Latest open access articles published in Journal of Intelligent Systems and Control at https://www.acadlore.com/journals/JISC https://www.acadlore.com/journals/JISC Acadlore en Creative Commons Attribution(CC - BY) JISC support@acadlore.com https://www.acadlore.com/article/JISC/2025_4_2/jisc040203 A Bayesian framework for estimating finger joint kinematics from spatially tracked hand landmarks was introduced in this study. Three-dimensional landmark data were constructed by augmenting image-based two-dimensional hand landmarks with calibrated depth information. A hierarchy of coordinate frames was established, beginning with the palm as the root and extending to child frames assigned to each finger, thereby encoding the natural kinematic dependencies of the hand. This hierarchical representation provides the structural foundation for Bayesian estimation. Finger joint parameters were estimated within a maximum likelihood framework that is robust to tracking noise and signal occlusions, which are common in practical hand-tracking scenarios. Unlike data-driven methods, the proposed approach does not rely on pre-collected training datasets but instead leverages the kinematic model and intrinsic physical constraints of the human hand. The estimation problem was formalized as a Gaussian Bayesian Network (GBN), through which joint parameters were inferred using Maximum Likelihood Estimation (MLE). Robustness of the approach was qualitatively demonstrated through reconstructed graphical configurations that illustrate accurate recovery of finger postures under noisy conditions. This method provides a principled framework for hand motion reconstruction and establishes the foundation for future quantitative evaluations against benchmark datasets. The framework is expected to advance applications in human–computer interaction, prosthetic design, virtual reality (VR), and rehabilitation by enabling more reliable and anatomically consistent hand tracking. 06-29-2025 <![CDATA[ A Bayesian framework for estimating finger joint kinematics from spatially tracked hand landmarks was introduced in this study. Three-dimensional landmark data were constructed by augmenting image-based two-dimensional hand landmarks with calibrated depth information. A hierarchy of coordinate frames was established, beginning with the palm as the root and extending to child frames assigned to each finger, thereby encoding the natural kinematic dependencies of the hand. This hierarchical representation provides the structural foundation for Bayesian estimation. Finger joint parameters were estimated within a maximum likelihood framework that is robust to tracking noise and signal occlusions, which are common in practical hand-tracking scenarios. Unlike data-driven methods, the proposed approach does not rely on pre-collected training datasets but instead leverages the kinematic model and intrinsic physical constraints of the human hand. The estimation problem was formalized as a Gaussian Bayesian Network (GBN), through which joint parameters were inferred using Maximum Likelihood Estimation (MLE). Robustness of the approach was qualitatively demonstrated through reconstructed graphical configurations that illustrate accurate recovery of finger postures under noisy conditions. This method provides a principled framework for hand motion reconstruction and establishes the foundation for future quantitative evaluations against benchmark datasets. The framework is expected to advance applications in human–computer interaction, prosthetic design, virtual reality (VR), and rehabilitation by enabling more reliable and anatomically consistent hand tracking. ]]> Bayesian Estimation of Hand Kinematics from Spatially Tracked Landmarks yiyang dong shahram payandeh doi: 10.56578/jisc040203 Journal of Intelligent Systems and Control 06-29-2025 Journal of Intelligent Systems and Control 06-29-2025 2025 4 2 Article 105 10.56578/jisc040203 https://www.acadlore.com/article/JISC/2025_4_2/jisc040203 https://www.acadlore.com/article/JISC/2025_4_2/jisc040202 Two-wheeled self-balancing vehicles inherently exhibit nonlinear, unstable, and strongly coupled dynamic characteristics, and their analysis and control remain of substantial relevance to military, industrial, and intelligent transportation applications. To address these challenges, a Bluetooth-enabled self-balancing vehicle system was designed with enhanced sensing, estimation, and hierarchical control capabilities. An improved Kalman filter (KF) algorithm was developed to overcome the limitations of conventional sensor fusion approaches. In the proposed method, gyroscope and accelerometer measurements were adaptively fused, enabling higher accuracy in attitude estimation while suppressing cumulative drift and transient disturbances. On this basis, a hierarchical proportional–integral–derivative (PID) control strategy was formulated to enhance responsiveness, stability, and tunability. Optimal attitude angles and reference velocities were processed within this framework to generate pulse-width modulation (PWM) signals for motor actuation. In parallel, a Bluetooth module was integrated to receive real-time commands from a mobile application, enabling precise execution of forward motion, reverse motion, and differential steering maneuvers. Experimental validation demonstrated that the system maintained stable posture, resisted external perturbations, responded rapidly to mobile control inputs, and executed commanded trajectories with high accuracy. The overall performance indicates that the proposed design provides a reliable and scalable platform for self-balancing vehicle research and offers potential applicability in human-robot interaction, intelligent mobility, and adaptive control studies. 06-29-2025 <![CDATA[ Two-wheeled self-balancing vehicles inherently exhibit nonlinear, unstable, and strongly coupled dynamic characteristics, and their analysis and control remain of substantial relevance to military, industrial, and intelligent transportation applications. To address these challenges, a Bluetooth-enabled self-balancing vehicle system was designed with enhanced sensing, estimation, and hierarchical control capabilities. An improved Kalman filter (KF) algorithm was developed to overcome the limitations of conventional sensor fusion approaches. In the proposed method, gyroscope and accelerometer measurements were adaptively fused, enabling higher accuracy in attitude estimation while suppressing cumulative drift and transient disturbances. On this basis, a hierarchical proportional–integral–derivative (PID) control strategy was formulated to enhance responsiveness, stability, and tunability. Optimal attitude angles and reference velocities were processed within this framework to generate pulse-width modulation (PWM) signals for motor actuation. In parallel, a Bluetooth module was integrated to receive real-time commands from a mobile application, enabling precise execution of forward motion, reverse motion, and differential steering maneuvers. Experimental validation demonstrated that the system maintained stable posture, resisted external perturbations, responded rapidly to mobile control inputs, and executed commanded trajectories with high accuracy. The overall performance indicates that the proposed design provides a reliable and scalable platform for self-balancing vehicle research and offers potential applicability in human-robot interaction, intelligent mobility, and adaptive control studies. ]]> Design and Control of a Bluetooth-Enabled Two-Wheeled Self-Balancing Vehicle fuchun jiang huangjie guo chenwei feng xinjie yang yau hee kho doi: 10.56578/jisc040202 Journal of Intelligent Systems and Control 06-29-2025 Journal of Intelligent Systems and Control 06-29-2025 2025 4 2 Article 84 10.56578/jisc040202 https://www.acadlore.com/article/JISC/2025_4_2/jisc040202 https://www.acadlore.com/article/JISC/2025_4_2/jisc040201 An extended Gibbs-Appell (G-A) formulation is presented for the derivation of motion equations in variable-mass systems subject to holonomic and nonholonomic constraints. The formulation incorporates time-varying mass into the classical G-A framework, thereby enabling a rigorous treatment of dynamic systems in which mass distribution changes during operation. By employing quasi-velocities, the motion equations were expressed in a simplified form, eliminating the necessity of Lagrange multipliers. The methodology was demonstrated through the dynamic modeling of a mobile robot sprayer for precision agriculture, where the mass of the liquid tank decreased during spraying. In this application, wheeled motion constraints and joint mechanics were explicitly captured, allowing accurate representation of navigation and spraying dynamics. Numerical simulations were conducted in MATLAB, where a proportional-integral-derivative (PID) control algorithm was implemented to follow a prescribed circular trajectory. The results indicate a mean tracking error of 0.2346 m and a mean orientation error of 0.0039 rad, confirming the robustness of the proposed framework. Beyond agricultural robotics, the extended G-A formulation establishes a versatile foundation for the analysis of constrained variable-mass systems in aerospace engineering, robotic mobility, and other domains where dynamic mass variation significantly influences system performance. 06-09-2025 <![CDATA[ An extended Gibbs-Appell (G-A) formulation is presented for the derivation of motion equations in variable-mass systems subject to holonomic and nonholonomic constraints. The formulation incorporates time-varying mass into the classical G-A framework, thereby enabling a rigorous treatment of dynamic systems in which mass distribution changes during operation. By employing quasi-velocities, the motion equations were expressed in a simplified form, eliminating the necessity of Lagrange multipliers. The methodology was demonstrated through the dynamic modeling of a mobile robot sprayer for precision agriculture, where the mass of the liquid tank decreased during spraying. In this application, wheeled motion constraints and joint mechanics were explicitly captured, allowing accurate representation of navigation and spraying dynamics. Numerical simulations were conducted in MATLAB, where a proportional-integral-derivative (PID) control algorithm was implemented to follow a prescribed circular trajectory. The results indicate a mean tracking error of 0.2346 m and a mean orientation error of 0.0039 rad, confirming the robustness of the proposed framework. Beyond agricultural robotics, the extended G-A formulation establishes a versatile foundation for the analysis of constrained variable-mass systems in aerospace engineering, robotic mobility, and other domains where dynamic mass variation significantly influences system performance. ]]> Motion Equation Derivation for Constrained Variable-Mass Systems Using the Extended Gibbs-Appell Formulation siavash fathollahi dehkordi doi: 10.56578/jisc040201 Journal of Intelligent Systems and Control 06-09-2025 Journal of Intelligent Systems and Control 06-09-2025 2025 4 2 Article 68 10.56578/jisc040201 https://www.acadlore.com/article/JISC/2025_4_2/jisc040201 https://www.acadlore.com/article/JISC/2025_4_1/jisc040105 Flapping wing robots (FWRs), inspired by the complex aerodynamics of birds, insects, and bats, have garnered substantial interest in recent years due to their ability to replicate agile and energy-efficient flight behaviors observed in nature. These biologically inspired aerial platforms are capable of executing sophisticated maneuvers, including stable hovering and rapid directional changes, which are typically unattainable by conventional rotary or fixed-wing aircraft. Attitude control systems, which are essential for ensuring flight stability across diverse environmental conditions, have undergone significant advancements with the integration of lightweight materials, novel actuation mechanisms, and miniaturized sensory technologies. Despite these developments, challenges persist in achieving robust, energy-efficient flight control under dynamically changing aerodynamic conditions. Bio-mimetic sensor technologies, such as gyroscopes, accelerometers, and tactile feedback systems, have been increasingly adopted to enable closed-loop feedback and real-time adaptive control. Both open-loop and closed-loop architectures have been investigated, with a growing emphasis on adaptive and learning-based control strategies to accommodate nonlinear flight dynamics. Recent research has explored the incorporation of artificial intelligence (AI) and machine learning (ML) algorithms to enhance autonomy, environmental adaptability, and decision-making capabilities. Despite these advances, limitations persist in power management, environmental robustness, and long-term flight endurance. Potential applications in surveillance, environmental monitoring, precision agriculture, and search-and-rescue missions underscore the transformative value of FWRs within autonomous aerial systems. Through continued interdisciplinary research in materials science, control theory, and computational intelligence, FWRs are anticipated to emerge as a pivotal class within the broader ecosystem of autonomous aerial systems. 03-30-2025 <![CDATA[ Flapping wing robots (FWRs), inspired by the complex aerodynamics of birds, insects, and bats, have garnered substantial interest in recent years due to their ability to replicate agile and energy-efficient flight behaviors observed in nature. These biologically inspired aerial platforms are capable of executing sophisticated maneuvers, including stable hovering and rapid directional changes, which are typically unattainable by conventional rotary or fixed-wing aircraft. Attitude control systems, which are essential for ensuring flight stability across diverse environmental conditions, have undergone significant advancements with the integration of lightweight materials, novel actuation mechanisms, and miniaturized sensory technologies. Despite these developments, challenges persist in achieving robust, energy-efficient flight control under dynamically changing aerodynamic conditions. Bio-mimetic sensor technologies, such as gyroscopes, accelerometers, and tactile feedback systems, have been increasingly adopted to enable closed-loop feedback and real-time adaptive control. Both open-loop and closed-loop architectures have been investigated, with a growing emphasis on adaptive and learning-based control strategies to accommodate nonlinear flight dynamics. Recent research has explored the incorporation of artificial intelligence (AI) and machine learning (ML) algorithms to enhance autonomy, environmental adaptability, and decision-making capabilities. Despite these advances, limitations persist in power management, environmental robustness, and long-term flight endurance. Potential applications in surveillance, environmental monitoring, precision agriculture, and search-and-rescue missions underscore the transformative value of FWRs within autonomous aerial systems. Through continued interdisciplinary research in materials science, control theory, and computational intelligence, FWRs are anticipated to emerge as a pivotal class within the broader ecosystem of autonomous aerial systems. ]]> Bio-Inspired Attitude Control in Flapping Wing Robots: Trends, Challenges, and Future Perspectives nibras m. mahdi ahmed adnan shandookh doi: 10.56578/jisc040105 Journal of Intelligent Systems and Control 03-30-2025 Journal of Intelligent Systems and Control 03-30-2025 2025 4 1 Article 48 10.56578/jisc040105 https://www.acadlore.com/article/JISC/2025_4_1/jisc040105 https://www.acadlore.com/article/JISC/2025_4_1/jisc040104 To address the time-delay and nonlinear characteristics of liquid level control in near-infrared spectroscopy-based liquid phase detection equipment, as well as the pipeline cavitation issues caused by improper sample pump speed settings during sample delivery—which may result in air bubble retention within the cuvette and subsequently degrade spectral data quality—a dual-buffer bottle sample delivery system model was established. A Proportional-Integral-Derivative (PID) controller was designed, and an enhanced hybrid algorithm integrating the Particle Swarm Optimization (PSO) algorithm and the Sparrow Search Algorithm (SSA) was proposed. The hybrid algorithm, referred to as the Adaptive Chaotic Mapping Particle Swarm Sparrow Algorithm (ACM-PSSA), incorporates Tent chaotic mapping for population initialization, a nonlinear cosine-based adaptive sparrow classification strategy, and a master–slave optimization mechanism wherein SSA performs global exploration and PSO executes local exploitation to optimize PID parameters. Simulation results demonstrate that ACM-PSSA outperforms traditional SSA and PSO across six benchmark test functions in terms of convergence speed, accuracy, and stability. When applied to the liquid level control of the dual-buffer bottle system, the optimized controller achieved a rise time of 0.188 seconds, a settling time of 1.211 seconds, and an overshoot reduced to 20.98%. By leveraging chaotic mapping, adaptive classification, and a master–slave optimization framework, ACM-PSSA effectively overcomes the limitations of conventional SSA and PSO, significantly enhancing the efficiency of PID parameter optimization and the overall control performance of the dual-buffer bottle sample delivery system. 03-30-2025 <![CDATA[ <p>To address the time-delay and nonlinear characteristics of liquid level control in near-infrared spectroscopy-based liquid phase detection equipment, as well as the pipeline cavitation issues caused by improper sample pump speed settings during sample delivery—which may result in air bubble retention within the cuvette and subsequently degrade spectral data quality—a dual-buffer bottle sample delivery system model was established. A Proportional-Integral-Derivative (PID) controller was designed, and an enhanced hybrid algorithm integrating the Particle Swarm Optimization (PSO) algorithm and the Sparrow Search Algorithm (SSA) was proposed. The hybrid algorithm, referred to as the Adaptive Chaotic Mapping Particle Swarm Sparrow Algorithm (ACM-PSSA), incorporates Tent chaotic mapping for population initialization, a nonlinear cosine-based adaptive sparrow classification strategy, and a master–slave optimization mechanism wherein SSA performs global exploration and PSO executes local exploitation to optimize PID parameters. Simulation results demonstrate that ACM-PSSA outperforms traditional SSA and PSO across six benchmark test functions in terms of convergence speed, accuracy, and stability. When applied to the liquid level control of the dual-buffer bottle system, the optimized controller achieved a rise time of 0.188 seconds, a settling time of 1.211 seconds, and an overshoot reduced to 20.98%. By leveraging chaotic mapping, adaptive classification, and a master–slave optimization framework, ACM-PSSA effectively overcomes the limitations of conventional SSA and PSO, significantly enhancing the efficiency of PID parameter optimization and the overall control performance of the dual-buffer bottle sample delivery system.</p> ]]> Optimized Liquid Level Control in Near-Infrared Spectroscopy-Based Liquid Phase Detection Equipment Using a PSSA-PID Approach yongshun wei guiqing xi shiqin peng yuhao lu ling yu doi: 10.56578/jisc040104 Journal of Intelligent Systems and Control 03-30-2025 Journal of Intelligent Systems and Control 03-30-2025 2025 4 1 Article 34 10.56578/jisc040104 https://www.acadlore.com/article/JISC/2025_4_1/jisc040104 https://www.acadlore.com/article/JISC/2025_4_1/jisc040103 Permanent Magnet Synchronous Motors (PMSMs) have garnered sustained attention over the past four decades due to their high efficiency, superior torque density, and dependable operational characteristics, making them highly suitable for a wide range of industrial applications. Accurate dynamic modelling of PMSMs is essential for performance evaluation and the development of advanced drive control strategies. Although previous studies have addressed customized modelling approaches for various PMSM types, a streamlined method for deriving model parameters from standard manufacturer specifications remains insufficiently explored. As a result, simulation studies are often disconnected from commercially available motor data, thereby limiting their practical relevance. In this study, the dynamic model of a PMSM is reformulated within the synchronous rotating reference frame (d-q axis) and implemented using mathematical function blocks in the MATLAB/Simulink environment. A systematic procedure is developed to extract key motor parameters from typical manufacturer data sheets. This approach bridges the gap between theoretical modeling and real-world motor implementation. The proposed modelling framework is validated using a standard 1 hp, 2.2 Nm, 1500 rpm PMSM, and its performance is benchmarked against the built-in Simulink PMSM blockset. Simulations are conducted to evaluate the mechanical output, rotor speed, and electromagnetic torque responses under step variations in load torque. The results exhibited strong agreement between the custom mathematical model and the blockset counterpart, confirming the accuracy and practical applicability of the parameter extraction methodology. 03-30-2025 <![CDATA[ Permanent Magnet Synchronous Motors (PMSMs) have garnered sustained attention over the past four decades due to their high efficiency, superior torque density, and dependable operational characteristics, making them highly suitable for a wide range of industrial applications. Accurate dynamic modelling of PMSMs is essential for performance evaluation and the development of advanced drive control strategies. Although previous studies have addressed customized modelling approaches for various PMSM types, a streamlined method for deriving model parameters from standard manufacturer specifications remains insufficiently explored. As a result, simulation studies are often disconnected from commercially available motor data, thereby limiting their practical relevance. In this study, the dynamic model of a PMSM is reformulated within the synchronous rotating reference frame (d-q axis) and implemented using mathematical function blocks in the MATLAB/Simulink environment. A systematic procedure is developed to extract key motor parameters from typical manufacturer data sheets. This approach bridges the gap between theoretical modeling and real-world motor implementation. The proposed modelling framework is validated using a standard 1 hp, 2.2 Nm, 1500 rpm PMSM, and its performance is benchmarked against the built-in Simulink PMSM blockset. Simulations are conducted to evaluate the mechanical output, rotor speed, and electromagnetic torque responses under step variations in load torque. The results exhibited strong agreement between the custom mathematical model and the blockset counterpart, confirming the accuracy and practical applicability of the parameter extraction methodology. ]]> Dynamic Modelling of Permanent Magnet Synchronous Motors with Graphical Simulation Validation s. jasphin melba a. ravi shibu j. v. bright doi: 10.56578/jisc040103 Journal of Intelligent Systems and Control 03-30-2025 Journal of Intelligent Systems and Control 03-30-2025 2025 4 1 Article 21 10.56578/jisc040103 https://www.acadlore.com/article/JISC/2025_4_1/jisc040103 https://www.acadlore.com/article/JISC/2025_4_1/jisc040102 Efficient bidirectional energy exchange between an alternating current (AC) grid and a direct current (DC) source has been enabled through advanced power converter topologies. In this study, a single-stage AC-DC dual active bridge (DAB) converter employing phase-shift modulation (PSM) was investigated, with a particular focus on performance within the overmodulation regime. Bidirectional switching modules were implemented on the AC side to facilitate seamless energy transfer. Two conventional modulation strategies—sinusoidal and triangular—and a novel back-calculated modulation method were examined for their performance in both linear and overmodulation operating regions. The proposed back-calculation method incorporates an off-line generated reference current waveform designed to approximate linear control characteristics while substantially minimizing current harmonic distortion under overmodulated conditions. This approach extends the linear relationship between the reference current and power transfer capability beyond the conventional modulation limits, thereby enhancing converter performance in high-demand scenarios. Simulation-based analysis demonstrated that, in the linear region, the proposed method reduced average current total harmonic distortion (THD) by at least 45% when compared to conventional sinusoidal and triangular modulation techniques. Moreover, within the overmodulation regime, the linear correlation between the reference current and power transfer was extended by approximately 16.5%. The current harmonic distortion remained below 5% and 8% at modulation ratios of 108% and 112%, respectively, underscoring the robustness of the proposed strategy. These results suggest that the proposed PSM method is highly effective in achieving improved power exchange with reduced harmonic content in both linear and overmodulated operation, thereby offering a viable solution for high-performance AC-DC power conversion in smart grids and renewable energy systems. 03-30-2025 <![CDATA[ <p>Efficient bidirectional energy exchange between an alternating current (AC) grid and a direct current (DC) source has been enabled through advanced power converter topologies. In this study, a single-stage AC-DC dual active bridge (DAB) converter employing phase-shift modulation (PSM) was investigated, with a particular focus on performance within the overmodulation regime. Bidirectional switching modules were implemented on the AC side to facilitate seamless energy transfer. Two conventional modulation strategies—sinusoidal and triangular—and a novel back-calculated modulation method were examined for their performance in both linear and overmodulation operating regions. The proposed back-calculation method incorporates an off-line generated reference current waveform designed to approximate linear control characteristics while substantially minimizing current harmonic distortion under overmodulated conditions. This approach extends the linear relationship between the reference current and power transfer capability beyond the conventional modulation limits, thereby enhancing converter performance in high-demand scenarios. Simulation-based analysis demonstrated that, in the linear region, the proposed method reduced average current total harmonic distortion (THD) by at least 45% when compared to conventional sinusoidal and triangular modulation techniques. Moreover, within the overmodulation regime, the linear correlation between the reference current and power transfer was extended by approximately 16.5%. The current harmonic distortion remained below 5% and 8% at modulation ratios of 108% and 112%, respectively, underscoring the robustness of the proposed strategy. These results suggest that the proposed PSM method is highly effective in achieving improved power exchange with reduced harmonic content in both linear and overmodulated operation, thereby offering a viable solution for high-performance AC-DC power conversion in smart grids and renewable energy systems.</p> ]]> Phase Shift Modulation Control of Single Stage Dual Active Bridge AC to DC Converter in Overmodulation Region maha f. ahmed mohamad n. abdul kadir doi: 10.56578/jisc040102 Journal of Intelligent Systems and Control 03-30-2025 Journal of Intelligent Systems and Control 03-30-2025 2025 4 1 Article 10 10.56578/jisc040102 https://www.acadlore.com/article/JISC/2025_4_1/jisc040102 https://www.acadlore.com/article/JISC/2025_4_1/jisc040101 In recent decades, the strategic placement of capacitors for compensating inductive reactive power has been extensively investigated by network operators and researchers globally, owing to its profound impact on minimizing power losses, improving voltage regulation, and enhancing overall voltage stability. The installation of shunt capacitors has been demonstrated to significantly improve the efficiency and performance of power systems by regulating voltage levels at load points, as well as at distribution and transmission system buses. This approach not only reduces inductive reactive power but also corrects the system’s power factor, thereby optimizing energy utilization. In this study, the optimal sizing and placement of capacitor banks within a specific section of the Duhok city distribution network were systematically analyzed. The Electrical Transient Analyzer Program (ETAP) software was employed to simulate and evaluate power losses and voltage drops both before and after capacitor installation. The findings reveal a marked improvement in the voltage profile across the network, accompanied by a substantial reduction in power losses. These results underscore the critical role of capacitor banks in enhancing the operational efficiency of distribution networks, providing a robust framework for future implementations in similar systems. The methodology and outcomes presented herein offer valuable insights for network operators seeking to optimize power system performance through reactive power compensation. 03-25-2025 <![CDATA[ <p>In recent decades, the strategic placement of capacitors for compensating inductive reactive power has been extensively investigated by network operators and researchers globally, owing to its profound impact on minimizing power losses, improving voltage regulation, and enhancing overall voltage stability. The installation of shunt capacitors has been demonstrated to significantly improve the efficiency and performance of power systems by regulating voltage levels at load points, as well as at distribution and transmission system buses. This approach not only reduces inductive reactive power but also corrects the system’s power factor, thereby optimizing energy utilization. In this study, the optimal sizing and placement of capacitor banks within a specific section of the Duhok city distribution network were systematically analyzed. The Electrical Transient Analyzer Program (ETAP) software was employed to simulate and evaluate power losses and voltage drops both before and after capacitor installation. The findings reveal a marked improvement in the voltage profile across the network, accompanied by a substantial reduction in power losses. These results underscore the critical role of capacitor banks in enhancing the operational efficiency of distribution networks, providing a robust framework for future implementations in similar systems. The methodology and outcomes presented herein offer valuable insights for network operators seeking to optimize power system performance through reactive power compensation.</p> ]]> The Impact of Optimal Sizing and Placement of Capacitor Banks in Distribution Networks: Enhancing Voltage Profiles and Reducing Power Losses emad hussen sadiq rakan khalil antar doi: 10.56578/jisc040101 Journal of Intelligent Systems and Control 03-25-2025 Journal of Intelligent Systems and Control 03-25-2025 2025 4 1 Article 1 10.56578/jisc040101 https://www.acadlore.com/article/JISC/2025_4_1/jisc040101 https://www.acadlore.com/article/JISC/2024_3_4/jisc030405 The ability of neural network-based control systems for trajectory tracking in wheeled mobile vehicles was evaluated in this study. A significant challenge often encountered is the deviation from the desired trajectory, particularly in high-speed motion. A robust control scheme, designed using the Nonlinear Auto-Regressive Moving Average-Level 2 (NARMA-L2) approach, was employed to enhance the tracking performance under dynamic conditions. The NARMA-L2 controller, a well-established technique for nonlinear systems, was utilized to improve the accuracy and robustness of trajectory tracking in the presence of external disturbances and noise. In heavy-duty mobile vehicles, such as agricultural machines, maintaining straight-line motion at high speeds is particularly susceptible to external load effects and system noise. The proposed control strategy integrates several stages, including system modeling, controller design, and the training of the neural network. To optimize the parameters of a proportional-integral-derivative (PID) controller, the Particle Swarm Optimization (PSO) algorithm was applied, ensuring precise regulation of the vehicle’s speed. The controller generates a reference velocity, which is fed as a signal to control the motion of the left and right wheels, enabling effective steering and trajectory adherence. Simulation results demonstrate the effectiveness of the proposed controller in mitigating the impact of disturbances and load effects. The optimization of control parameters successfully minimizes the discrepancy between the left and right wheel positions, bringing them closer to zero. The robust parameter optimization approach, which was employed to counteract the influence of external loads, can significantly improve system performance under varying conditions. 12-30-2024 <![CDATA[ The ability of neural network-based control systems for trajectory tracking in wheeled mobile vehicles was evaluated in this study. A significant challenge often encountered is the deviation from the desired trajectory, particularly in high-speed motion. A robust control scheme, designed using the Nonlinear Auto-Regressive Moving Average-Level 2 (NARMA-L2) approach, was employed to enhance the tracking performance under dynamic conditions. The NARMA-L2 controller, a well-established technique for nonlinear systems, was utilized to improve the accuracy and robustness of trajectory tracking in the presence of external disturbances and noise. In heavy-duty mobile vehicles, such as agricultural machines, maintaining straight-line motion at high speeds is particularly susceptible to external load effects and system noise. The proposed control strategy integrates several stages, including system modeling, controller design, and the training of the neural network. To optimize the parameters of a proportional-integral-derivative (PID) controller, the Particle Swarm Optimization (PSO) algorithm was applied, ensuring precise regulation of the vehicle’s speed. The controller generates a reference velocity, which is fed as a signal to control the motion of the left and right wheels, enabling effective steering and trajectory adherence. Simulation results demonstrate the effectiveness of the proposed controller in mitigating the impact of disturbances and load effects. The optimization of control parameters successfully minimizes the discrepancy between the left and right wheel positions, bringing them closer to zero. The robust parameter optimization approach, which was employed to counteract the influence of external loads, can significantly improve system performance under varying conditions. ]]> Robust Neural Network-Based Trajectory Tracking Control for Mobile Vehicles hasan h. juhi nihad m. ameen sarab a. mahmood yousra abd mohammed ammar a. yahya doi: 10.56578/jisc030405 Journal of Intelligent Systems and Control 12-30-2024 Journal of Intelligent Systems and Control 12-30-2024 2024 3 4 Article 251 10.56578/jisc030405 https://www.acadlore.com/article/JISC/2024_3_4/jisc030405 https://www.acadlore.com/article/JISC/2024_3_4/jisc030404 Accurate monitoring of turbine speed is essential for ensuring operational stability and efficiency in power generation systems, particularly within the context of low-carbon and renewable energy integration. This study evaluates the performance of three Variable Reluctance Sensors (VRSs)—VRS1, VRS2, and VRS3—used for real-time speed monitoring of the Steam Turbine Generator (STG) 1.0 at the Tambak Lorok Combined Cycle Power Plant (CCPP). The evaluation was conducted using statistical methods, including Root Mean Square Error (RMSE), standard deviation, and two-factor Analysis of Variance (ANOVA) without replication, to assess the accuracy and consistency of the sensors under varying operational conditions. The operational conditions were simulated through a motor controlled by a Variable Speed Drive (VSD), which allows for precise control over speed variations. The results indicate that the VRSs exhibit high accuracy and reliability, with RMSE values ranging from 0.08% to 0.28%. Among the three sensors, VRS3 demonstrated the highest performance, achieving minimal variability, with a standard deviation of 0.000 at a frequency of 50.00 Hz. ANOVA revealed no significant differences in performance between the three sensors (P-value = 1.000), suggesting uniformity in their measurement capabilities. These findings substantiate the suitability of VRSs for turbine speed monitoring in power plants, ensuring operational stability and supporting the integration of renewable energy technologies. The results reinforce the potential of VRSs as a reliable tool for improving the efficiency of sustainable energy systems 12-30-2024 <![CDATA[ <p>Accurate monitoring of turbine speed is essential for ensuring operational stability and efficiency in power generation systems, particularly within the context of low-carbon and renewable energy integration. This study evaluates the performance of three Variable Reluctance Sensors (VRSs)—VRS1, VRS2, and VRS3—used for real-time speed monitoring of the Steam Turbine Generator (STG) 1.0 at the Tambak Lorok Combined Cycle Power Plant (CCPP). The evaluation was conducted using statistical methods, including Root Mean Square Error (RMSE), standard deviation, and two-factor Analysis of Variance (ANOVA) without replication, to assess the accuracy and consistency of the sensors under varying operational conditions. The operational conditions were simulated through a motor controlled by a Variable Speed Drive (VSD), which allows for precise control over speed variations. The results indicate that the VRSs exhibit high accuracy and reliability, with RMSE values ranging from 0.08% to 0.28%. Among the three sensors, VRS3 demonstrated the highest performance, achieving minimal variability, with a standard deviation of 0.000 at a frequency of 50.00 Hz. ANOVA revealed no significant differences in performance between the three sensors (P-value = 1.000), suggesting uniformity in their measurement capabilities. These findings substantiate the suitability of VRSs for turbine speed monitoring in power plants, ensuring operational stability and supporting the integration of renewable energy technologies. The results reinforce the potential of VRSs as a reliable tool for improving the efficiency of sustainable energy systems</p> ]]> Evaluation of the Accuracy and Consistency of Variable Reluctance Sensors for Turbine Speed Monitoring in Steam Turbine Generator 1.0 at Tambak Lorok CCPP afif abdul hadi ahmad azmi fikri doi: 10.56578/jisc030404 Journal of Intelligent Systems and Control 12-30-2024 Journal of Intelligent Systems and Control 12-30-2024 2024 3 4 Article 239 10.56578/jisc030404 https://www.acadlore.com/article/JISC/2024_3_4/jisc030404 https://www.acadlore.com/article/JISC/2024_3_4/jisc030403 The growing demand for energy, driven by urbanization and environmental concerns, has highlighted the need for innovative solutions in power management, particularly within residential and small business settings. This study presents a comprehensive smart home automation system, which is based on Internet of Things (IoT), designed to address these challenges. By integrating a smartphone application with Arduino-based hardware, the proposed system enables real-time remote operation, scheduling, and monitoring of electrical appliances. Bluetooth connectivity, coupled with advanced coding techniques, was employed to accurately measure power consumption and compute associated costs. The system's user interface was evaluated for its ease of use, responsiveness, and high accuracy, providing users with the ability to track energy usage trends, optimize appliance operation, and make informed decisions regarding energy consumption and cost management. Furthermore, the solution promotes sustainable energy practices by facilitating the reduction of unnecessary energy consumption. This scalable, cost-effective approach is poised to support the broader adoption of energy-efficient technologies. Future enhancements, such as integration with voice assistants and the addition of Wi-Fi connectivity, are expected to further expand the system's capabilities. The findings demonstrate the significant potential of IoT technologies to transform energy management and foster environmentally conscious behavior in smart homes. 12-29-2024 <![CDATA[ The growing demand for energy, driven by urbanization and environmental concerns, has highlighted the need for innovative solutions in power management, particularly within residential and small business settings. This study presents a comprehensive smart home automation system, which is based on Internet of Things (IoT), designed to address these challenges. By integrating a smartphone application with Arduino-based hardware, the proposed system enables real-time remote operation, scheduling, and monitoring of electrical appliances. Bluetooth connectivity, coupled with advanced coding techniques, was employed to accurately measure power consumption and compute associated costs. The system's user interface was evaluated for its ease of use, responsiveness, and high accuracy, providing users with the ability to track energy usage trends, optimize appliance operation, and make informed decisions regarding energy consumption and cost management. Furthermore, the solution promotes sustainable energy practices by facilitating the reduction of unnecessary energy consumption. This scalable, cost-effective approach is poised to support the broader adoption of energy-efficient technologies. Future enhancements, such as integration with voice assistants and the addition of Wi-Fi connectivity, are expected to further expand the system's capabilities. The findings demonstrate the significant potential of IoT technologies to transform energy management and foster environmentally conscious behavior in smart homes. ]]> Integration of IoT for Smart Energy Management: Advancing Home Automation and Power Efficiency sayak mukhopadhyay janmejay gupta akshay kumar doi: 10.56578/jisc030403 Journal of Intelligent Systems and Control 12-29-2024 Journal of Intelligent Systems and Control 12-29-2024 2024 3 4 Article 227 10.56578/jisc030403 https://www.acadlore.com/article/JISC/2024_3_4/jisc030403 https://www.acadlore.com/article/JISC/2024_3_4/jisc030402 A novel approach for road crack detection and segmentation was proposed, incorporating Einstein operators within an Adaptive Neuro-Fuzzy Inference System (ANFIS). This methodology leverages advanced fuzzy aggregation techniques and adaptive mechanisms, combined with dynamic Einstein sum and product operators, to enhance the identification of cracks. The model was designed to effectively manage varying crack intensities, geometries, and noise levels, thereby ensuring high sensitivity and accuracy in real-world road conditions. In the preprocessing stage, robust fuzzification was applied using Gaussian membership functions alongside Einstein operators, which significantly improved feature extraction. The segmentation framework based on ANFIS ensured precise detection and delineation of cracks. The performance of the proposed model was demonstrated through a comparative analysis, showing superior accuracy (95.2%), precision (94.1%), recall (96.4%), and F1-score (95.2%) when compared to state-of-the-art models. Statistical validation was conducted, with p-values 12-25-2024 <![CDATA[ <p>A novel approach for road crack detection and segmentation was proposed, incorporating Einstein operators within an Adaptive Neuro-Fuzzy Inference System (ANFIS). This methodology leverages advanced fuzzy aggregation techniques and adaptive mechanisms, combined with dynamic Einstein sum and product operators, to enhance the identification of cracks. The model was designed to effectively manage varying crack intensities, geometries, and noise levels, thereby ensuring high sensitivity and accuracy in real-world road conditions. In the preprocessing stage, robust fuzzification was applied using Gaussian membership functions alongside Einstein operators, which significantly improved feature extraction. The segmentation framework based on ANFIS ensured precise detection and delineation of cracks. The performance of the proposed model was demonstrated through a comparative analysis, showing superior accuracy (95.2%), precision (94.1%), recall (96.4%), and F1-score (95.2%) when compared to state-of-the-art models. Statistical validation was conducted, with p-values < 0.01 for all performance metrics, confirming the reliability and statistical significance of the results. Advanced post-processing techniques, including fuzzy morphological refinement and adjacency matrix-based connectivity analysis, were employed to accurately identify even faint or disconnected cracks. The proposed method exhibits exceptional resilience to environmental variations, offering a reliable and adaptive solution for road maintenance and monitoring. This work highlights the potential of fuzzy logic, statistical validation, and adaptive mechanisms in addressing real-world challenges in road crack detection.</p> ]]> Adaptive Road Crack Detection and Segmentation Using Einstein Operators and ANFIS for Real-Time Applications ibrar hussain luqman alam doi: 10.56578/jisc030402 Journal of Intelligent Systems and Control 12-25-2024 Journal of Intelligent Systems and Control 12-25-2024 2024 3 4 Article 213 10.56578/jisc030402 https://www.acadlore.com/article/JISC/2024_3_4/jisc030402 https://www.acadlore.com/article/JISC/2024_3_4/jisc030401 A three-degree-of-freedom air-floating simulation platform is commonly used for attitude maneuver simulation and control system design. To reduce the impact of gravity on the air-floating platform, adjustments must be made to the platform's center of mass so that it coincides as closely as possible with the center of rotation (CR). For larger three-degree-of-freedom platforms, it is often different to easily obtain the moment of inertia, which presents challenges for automatic leveling. In response to this issue, an automatic leveling method was proposed in this study. This method utilizes attitude and angular velocity information, and during the leveling process, only a linear motion mechanism is required to drive a mass block for adjustment. An analysis of the uncertainties present in the model was conducted, and the uncertainties in the system were processed separately. Adaptive control techniques were then applied to design the control method. The stability of the system was demonstrated through the Lyapunov stability theorem. Finally, the algorithm was tested on a three-degree-of-freedom air-floating platform. The experimental results showed that the proposed method can achieve rapid and effective leveling of the platform. 12-23-2024 <![CDATA[ A three-degree-of-freedom air-floating simulation platform is commonly used for attitude maneuver simulation and control system design. To reduce the impact of gravity on the air-floating platform, adjustments must be made to the platform's center of mass so that it coincides as closely as possible with the center of rotation (CR). For larger three-degree-of-freedom platforms, it is often different to easily obtain the moment of inertia, which presents challenges for automatic leveling. In response to this issue, an automatic leveling method was proposed in this study. This method utilizes attitude and angular velocity information, and during the leveling process, only a linear motion mechanism is required to drive a mass block for adjustment. An analysis of the uncertainties present in the model was conducted, and the uncertainties in the system were processed separately. Adaptive control techniques were then applied to design the control method. The stability of the system was demonstrated through the Lyapunov stability theorem. Finally, the algorithm was tested on a three-degree-of-freedom air-floating platform. The experimental results showed that the proposed method can achieve rapid and effective leveling of the platform. ]]> Automatic Leveling Algorithm for a Three-Degree-of-Freedom Air-Floating Platform with Uncertain Inertia qingtao hou xuexu yuan junwei zhao yuanyuan zhang hanyu gao xiaowei fu doi: 10.56578/jisc030401 Journal of Intelligent Systems and Control 12-23-2024 Journal of Intelligent Systems and Control 12-23-2024 2024 3 4 Article 201 10.56578/jisc030401 https://www.acadlore.com/article/JISC/2024_3_4/jisc030401 https://www.acadlore.com/article/JISC/2024_3_3/jisc030305 Indonesia, a significant exporter of coffee, faces persistent challenges in accurately identifying and classifying coffee varieties based on aromatic characteristics, primarily due to the subjective variability of human sensory evaluation. To address these limitations, an electronic nose (e-nose) system was developed for the classification of coffee varieties through the analysis of aromatic profiles. The system integrates a DHT-22 sensor and four gas sensors (MQ-5, MQ-4, MQ-3, and MQ-135) to measure humidity, temperature, and gas concentrations from coffee vapor. Data acquisition was facilitated by the Arduino Uno platform, while classification was conducted using the Naive Bayes Classifier (NBC) algorithm. The e-nose achieved a classification accuracy of 82.2%, as validated through a confusion matrix and performance metrics, including precision, recall, and F1-score. Among the gas sensors employed, the MQ-4 sensor, which detects methane, demonstrated the highest response sensitivity, whereas the MQ-3 sensor, designed to detect alcohol, exhibited the lowest. This system significantly mitigates the inherent subjectivity associated with traditional aroma assessment methods and offers considerable potential for enhancing quality control protocols in coffee production processes. Future work will focus on integrating advanced machine-learning algorithms, optimizing sensor array performance, and expanding the dataset to include a broader diversity of coffee samples. These advancements are expected to further refine the system's classification capabilities and contribute to more robust quality assurance in the coffee industry. 09-29-2024 <![CDATA[ <p>Indonesia, a significant exporter of coffee, faces persistent challenges in accurately identifying and classifying coffee varieties based on aromatic characteristics, primarily due to the subjective variability of human sensory evaluation. To address these limitations, an electronic nose (e-nose) system was developed for the classification of coffee varieties through the analysis of aromatic profiles. The system integrates a DHT-22 sensor and four gas sensors (MQ-5, MQ-4, MQ-3, and MQ-135) to measure humidity, temperature, and gas concentrations from coffee vapor. Data acquisition was facilitated by the Arduino Uno platform, while classification was conducted using the Naive Bayes Classifier (NBC) algorithm. The e-nose achieved a classification accuracy of 82.2%, as validated through a confusion matrix and performance metrics, including precision, recall, and F1-score. Among the gas sensors employed, the MQ-4 sensor, which detects methane, demonstrated the highest response sensitivity, whereas the MQ-3 sensor, designed to detect alcohol, exhibited the lowest. This system significantly mitigates the inherent subjectivity associated with traditional aroma assessment methods and offers considerable potential for enhancing quality control protocols in coffee production processes. Future work will focus on integrating advanced machine-learning algorithms, optimizing sensor array performance, and expanding the dataset to include a broader diversity of coffee samples. These advancements are expected to further refine the system's classification capabilities and contribute to more robust quality assurance in the coffee industry.</p> ]]> Development and Application of an Electronic Nose System for Classifying Coffee Varieties Based on Aromatic Profiles danang erwanto royb fatkhur rizal dian efytra yuliana misbahul munir yuki trisnoaji catur harsito abram anggit mahadi singgih dwi prasetyo doi: 10.56578/jisc030305 Journal of Intelligent Systems and Control 09-29-2024 Journal of Intelligent Systems and Control 09-29-2024 2024 3 3 Article 186 10.56578/jisc030305 https://www.acadlore.com/article/JISC/2024_3_3/jisc030305 https://www.acadlore.com/article/JISC/2024_3_3/jisc030304 The environmental conditions in large-scale, intensive poultry farming systems require high precision, and accurate prediction of environmental factors is critical for effective control. Existing control methods generally focus on the prediction and control of individual environmental factors without considering the interdependencies among these factors, leading to low prediction and control accuracy. To address the complex nature of the environmental system in poultry houses, characterised by multi-factor dependencies, an adaptive environmental control system based on Multi-feature Long Short-Term Memory (Multif-LSTM) was proposed. The Multif-LSTM model within the system calculates the dependencies between environmental factors using correlation coefficients and establishes a multi-input, multi-output neural network architecture. External climate factors are also incorporated during the input phase. Experimental comparisons conducted in a duck house environment, with Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) models, show that the Multif-LSTM model outperforms others in terms of prediction accuracy. For NH3 concentration, the Root Mean Square Error (RMSE), the Mean Absolute Percentage Error (MAPE), and Coefficient of Determination (R2) values are 1.34, 8.3, and 0.55, respectively; for temperature, they are 0.29, 2.83, and 0.98; and for relative humidity, they are 1.73, 2.46, and 0.95, respectively. Compared to the average performance of the RNN and LSTM models, the RMSE is reduced by 2.5, MAPE by 4.6, and R2 increased by 0.32. The results demonstrate that the Multif-LSTM model achieves higher prediction accuracy and is suitable for high-precision adaptive environmental control in poultry houses. 09-29-2024 <![CDATA[ <p>The environmental conditions in large-scale, intensive poultry farming systems require high precision, and accurate prediction of environmental factors is critical for effective control. Existing control methods generally focus on the prediction and control of individual environmental factors without considering the interdependencies among these factors, leading to low prediction and control accuracy. To address the complex nature of the environmental system in poultry houses, characterised by multi-factor dependencies, an adaptive environmental control system based on Multi-feature Long Short-Term Memory (Multif-LSTM) was proposed. The Multif-LSTM model within the system calculates the dependencies between environmental factors using correlation coefficients and establishes a multi-input, multi-output neural network architecture. External climate factors are also incorporated during the input phase. Experimental comparisons conducted in a duck house environment, with Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) models, show that the Multif-LSTM model outperforms others in terms of prediction accuracy. For NH₃ concentration, the Root Mean Square Error (RMSE), the Mean Absolute Percentage Error (MAPE), and Coefficient of Determination (R²) values are 1.34, 8.3, and 0.55, respectively; for temperature, they are 0.29, 2.83, and 0.98; and for relative humidity, they are 1.73, 2.46, and 0.95, respectively. Compared to the average performance of the RNN and LSTM models, the RMSE is reduced by 2.5, MAPE by 4.6, and R² increased by 0.32. The results demonstrate that the Multif-LSTM model achieves higher prediction accuracy and is suitable for high-precision adaptive environmental control in poultry houses.</p> ]]> Adaptive Environmental Control System for Large-Scale Poultry Houses Based on Multif-LSTM lin zhang jialin ma ashim khadka doi: 10.56578/jisc030304 Journal of Intelligent Systems and Control 09-29-2024 Journal of Intelligent Systems and Control 09-29-2024 2024 3 3 Article 174 10.56578/jisc030304 https://www.acadlore.com/article/JISC/2024_3_3/jisc030304 https://www.acadlore.com/article/JISC/2024_3_3/jisc030303 To address the rate mismatch between high-bandwidth, high-sampling-rate analog-to-digital converters (ADCs) and low-bandwidth, low-sampling-rate baseband processors, digital signal processing techniques were employed to enable the parallel processing of broadband signals. The broadband signals were decomposed into multiple narrowband channels, facilitating parallel processing and frequency-selective analysis of signals. The validity of the principle was verified through MATLAB modeling. A digital channelization Register Transfer Level (RTL) model was constructed on a Field-Programmable Gate Array (FPGA) using Verilog Hardware Description Language (HDL), implementing a pipelined parallel processing mechanism. The computational efficiency in Fast Fourier Transform (FFT) operations was improved by optimizing the processing flow. A digital channelization receiver application test board was developed using a domestically produced FMQL45T900 FPGA as the core component. Practical applications confirmed the correctness of the approach, with significant improvements in power efficiency compared to methods reported in existing literature, thereby enhancing overall parallel processing performance. This method demonstrates broad applicability in fields such as military communications, broadcasting, radar navigation systems, and more. 09-29-2024 <![CDATA[ To address the rate mismatch between high-bandwidth, high-sampling-rate analog-to-digital converters (ADCs) and low-bandwidth, low-sampling-rate baseband processors, digital signal processing techniques were employed to enable the parallel processing of broadband signals. The broadband signals were decomposed into multiple narrowband channels, facilitating parallel processing and frequency-selective analysis of signals. The validity of the principle was verified through MATLAB modeling. A digital channelization Register Transfer Level (RTL) model was constructed on a Field-Programmable Gate Array (FPGA) using Verilog Hardware Description Language (HDL), implementing a pipelined parallel processing mechanism. The computational efficiency in Fast Fourier Transform (FFT) operations was improved by optimizing the processing flow. A digital channelization receiver application test board was developed using a domestically produced FMQL45T900 FPGA as the core component. Practical applications confirmed the correctness of the approach, with significant improvements in power efficiency compared to methods reported in existing literature, thereby enhancing overall parallel processing performance. This method demonstrates broad applicability in fields such as military communications, broadcasting, radar navigation systems, and more. ]]> Design and Implementation of FPGA for Digital Channelization Processing ming yin yanlei fu jiefeng mei doi: 10.56578/jisc030303 Journal of Intelligent Systems and Control 09-29-2024 Journal of Intelligent Systems and Control 09-29-2024 2024 3 3 Article 160 10.56578/jisc030303 https://www.acadlore.com/article/JISC/2024_3_3/jisc030303 https://www.acadlore.com/article/JISC/2024_3_3/jisc030302 Underwater gliders have become a focal point in marine research due to advancements in maritime technologies and the increasing demand for versatile autonomous underwater vehicles (AUVs) in applications such as oceanography, environmental monitoring, and marine surveillance. This study provides a comprehensive analysis of the critical parameters influencing the gliding behavior of a newly designed AUV model, simulated using ANSYS Fluent. In this study, two essential gliding parameters were investigated: the critical angle of attack and the optimum wingspan. The model was fully submerged, and a three-dimensional representation of the AUV was employed to replicate realistic underwater dynamics. Navier-Stokes equations, coupled with continuity equations, were numerically solved to ensure mass and momentum conservation across the simulated environment. The model was rigorously validated against published experimental data, thereby establishing reliability in the simulated outcomes. The results reveal an optimum angle of attack that significantly enhances the glider’s maneuverability, facilitating efficient ascent and descent adjustments by the automated control system to navigate precise underwater positions. These findings contribute valuable insights for designing AUVs with enhanced autonomous control and efficient gliding capabilities, aiding in the effective application of AUVs across a range of marine environments. 09-29-2024 <![CDATA[ Underwater gliders have become a focal point in marine research due to advancements in maritime technologies and the increasing demand for versatile autonomous underwater vehicles (AUVs) in applications such as oceanography, environmental monitoring, and marine surveillance. This study provides a comprehensive analysis of the critical parameters influencing the gliding behavior of a newly designed AUV model, simulated using ANSYS Fluent. In this study, two essential gliding parameters were investigated: the critical angle of attack and the optimum wingspan. The model was fully submerged, and a three-dimensional representation of the AUV was employed to replicate realistic underwater dynamics. Navier-Stokes equations, coupled with continuity equations, were numerically solved to ensure mass and momentum conservation across the simulated environment. The model was rigorously validated against published experimental data, thereby establishing reliability in the simulated outcomes. The results reveal an optimum angle of attack that significantly enhances the glider’s maneuverability, facilitating efficient ascent and descent adjustments by the automated control system to navigate precise underwater positions. These findings contribute valuable insights for designing AUVs with enhanced autonomous control and efficient gliding capabilities, aiding in the effective application of AUVs across a range of marine environments. ]]> Critical Parameter Analysis for Optimized Gliding Performance of Autonomous Underwater Vehicles badar ul islam daim badar nasreen kausar doi: 10.56578/jisc030302 Journal of Intelligent Systems and Control 09-29-2024 Journal of Intelligent Systems and Control 09-29-2024 2024 3 3 Article 152 10.56578/jisc030302 https://www.acadlore.com/article/JISC/2024_3_3/jisc030302 https://www.acadlore.com/article/JISC/2024_3_3/jisc030301 Electricity remains one of the most vital resources for industrial, domestic, and agricultural applications. However, electricity theft has emerged as a significant challenge, contributing to substantial power losses and severe economic repercussions for utility companies. This study examines the role of smart meters (SMs) in minimizing electricity theft and reducing energy losses by transitioning from traditional analogue meters to advanced SMs equipped with automated billing and metering systems. Data collected from the SM system in the Akre energy distribution network reveal that, following the implementation of SMs, overall electrical power losses were reduced by 17.1%, while theft incidents decreased by 96.4%. These results demonstrate that the deployment of SMs significantly contributes to lowering total power losses and yields considerable financial benefits for both utility providers (UPs) and consumers. Moreover, the system enhances the ability to remotely monitor and control customer meters, allowing continuous oversight of meter readings without requiring physical visits. This remote functionality strengthens theft prevention measures, improves grid reliability, and reduces operational costs. The findings highlight the potential of the SM system in advancing power efficiency and promoting a more secure and cost-effective energy distribution network. 09-29-2024 <![CDATA[ <p>Electricity remains one of the most vital resources for industrial, domestic, and agricultural applications. However, electricity theft has emerged as a significant challenge, contributing to substantial power losses and severe economic repercussions for utility companies. This study examines the role of smart meters (SMs) in minimizing electricity theft and reducing energy losses by transitioning from traditional analogue meters to advanced SMs equipped with automated billing and metering systems. Data collected from the SM system in the Akre energy distribution network reveal that, following the implementation of SMs, overall electrical power losses were reduced by 17.1%, while theft incidents decreased by 96.4%. These results demonstrate that the deployment of SMs significantly contributes to lowering total power losses and yields considerable financial benefits for both utility providers (UPs) and consumers. Moreover, the system enhances the ability to remotely monitor and control customer meters, allowing continuous oversight of meter readings without requiring physical visits. This remote functionality strengthens theft prevention measures, improves grid reliability, and reduces operational costs. The findings highlight the potential of the SM system in advancing power efficiency and promoting a more secure and cost-effective energy distribution network.</p> ]]> Mitigating Non-Technical Losses and Electricity Theft Through Smart Meters: A Case Study of the Akre District Power Distribution Network nizar jabar faqishafyee emad hussen sadiq harwan m. taha doi: 10.56578/jisc030301 Journal of Intelligent Systems and Control 09-29-2024 Journal of Intelligent Systems and Control 09-29-2024 2024 3 3 Article 135 10.56578/jisc030301 https://www.acadlore.com/article/JISC/2024_3_3/jisc030301 https://www.acadlore.com/article/JISC/2024_3_2/jisc030205 The recognition of abnormal events in surveillance video streams plays a crucial role in modern security systems, yet conventional techniques such as Support Vector Machines (SVMs) and decision trees (DTs) exhibit limitations in terms of accuracy and efficiency. These traditional models are often hindered by high false alarm rates and struggle to adapt to dynamic environments with variable conditions, thus reducing their practical applicability. In response to these challenges, an innovative approach, termed Adaptive Regression for Event Recognition (ARER), has been developed, leveraging advanced regression algorithms tailored for video data analysis. The ARER model integrates deep learning techniques, allowing for more precise temporal and contextual analysis of video footage. This methodology is structured through a multi-layered architecture that progresses from basic motion detection to complex anomaly identification. Trained on an extensive dataset covering a range of environmental and situational variables, ARER demonstrates enhanced robustness and adaptability. Evaluation results indicate that the ARER model achieves a 0.35% improvement in detection accuracy and a 0.40% reduction in false positives when compared to SVMs. Additionally, system throughput is increased by 0.25%, and detection latency is reduced by 0.30% in comparison to DTs. These advancements highlight the ARER approach as a superior alternative for real-time monitoring, offering significant improvements in both reliability and performance for surveillance applications. 06-29-2024 <![CDATA[ <p>The recognition of abnormal events in surveillance video streams plays a crucial role in modern security systems, yet conventional techniques such as Support Vector Machines (SVMs) and decision trees (DTs) exhibit limitations in terms of accuracy and efficiency. These traditional models are often hindered by high false alarm rates and struggle to adapt to dynamic environments with variable conditions, thus reducing their practical applicability. In response to these challenges, an innovative approach, termed Adaptive Regression for Event Recognition (ARER), has been developed, leveraging advanced regression algorithms tailored for video data analysis. The ARER model integrates deep learning techniques, allowing for more precise temporal and contextual analysis of video footage. This methodology is structured through a multi-layered architecture that progresses from basic motion detection to complex anomaly identification. Trained on an extensive dataset covering a range of environmental and situational variables, ARER demonstrates enhanced robustness and adaptability. Evaluation results indicate that the ARER model achieves a 0.35% improvement in detection accuracy and a 0.40% reduction in false positives when compared to SVMs. Additionally, system throughput is increased by 0.25%, and detection latency is reduced by 0.30% in comparison to DTs. These advancements highlight the ARER approach as a superior alternative for real-time monitoring, offering significant improvements in both reliability and performance for surveillance applications.</p> ]]> Enhanced Abnormal Event Detection in Surveillance Videos Through Optimized Regression Algorithms jyothi honnegowda komala mallikarjunaiah mallikarjunaswamy srikantaswamy doi: 10.56578/jisc030205 Journal of Intelligent Systems and Control 06-29-2024 Journal of Intelligent Systems and Control 06-29-2024 2024 3 2 Article 121 10.56578/jisc030205 https://www.acadlore.com/article/JISC/2024_3_2/jisc030205 https://www.acadlore.com/article/JISC/2024_3_2/jisc030204 Separately excited direct current (DC) motors, renowned for their linear characteristics and controllability, are extensively employed in various industrial applications. Effective speed control of these motors can be achieved through multiple methods, with fuzzy logic being a particularly robust approach. This study focuses on evaluating the transient responses of current and voltage in relation to the rotational speed of a DC motor under two distinct control schemes: field control and armature control, both subjected to similar load disturbances. A simulation-based methodology was employed using a DC motor speed control system combined with a fuzzy logic controller (FLC) designed with the Mamdani min-max method. The system was implemented in Simulink. In this framework, the FLC processes speed error signals and field current ($I_f$) errors as inputs to generate a field voltage control signal, which is then utilized by the armature voltage (Va) regulator to modulate the armature voltage. The results demonstrate that the FLC effectively stabilizes motor speed, quickly and accurately following speed references, even under load disturbances. Moreover, the system effectively mitigates speed fluctuations induced by load variations. A comparison between the two control schemes reveals that the field control approach exhibits a slower response time, taking 2.93 seconds to reach a steady state, whereas the armature control achieves this in a significantly faster time of 0.144 seconds. These findings underscore the efficacy of fuzzy logic in maintaining stable and responsive speed control in DC motors, with the armature control method displaying superior transient performance. 06-29-2024 <![CDATA[ Separately excited direct current (DC) motors, renowned for their linear characteristics and controllability, are extensively employed in various industrial applications. Effective speed control of these motors can be achieved through multiple methods, with fuzzy logic being a particularly robust approach. This study focuses on evaluating the transient responses of current and voltage in relation to the rotational speed of a DC motor under two distinct control schemes: field control and armature control, both subjected to similar load disturbances. A simulation-based methodology was employed using a DC motor speed control system combined with a fuzzy logic controller (FLC) designed with the Mamdani min-max method. The system was implemented in Simulink. In this framework, the FLC processes speed error signals and field current ($I_f$) errors as inputs to generate a field voltage control signal, which is then utilized by the armature voltage (Va) regulator to modulate the armature voltage. The results demonstrate that the FLC effectively stabilizes motor speed, quickly and accurately following speed references, even under load disturbances. Moreover, the system effectively mitigates speed fluctuations induced by load variations. A comparison between the two control schemes reveals that the field control approach exhibits a slower response time, taking 2.93 seconds to reach a steady state, whereas the armature control achieves this in a significantly faster time of 0.144 seconds. These findings underscore the efficacy of fuzzy logic in maintaining stable and responsive speed control in DC motors, with the armature control method displaying superior transient performance. ]]> Comparison of Fuzzy Logic Controllers for Speed Regulation in Separately Excited DC Motors: Field Versus Armature Control sri kurniati sudirman syam nursalim wellem f. galla doi: 10.56578/jisc030204 Journal of Intelligent Systems and Control 06-29-2024 Journal of Intelligent Systems and Control 06-29-2024 2024 3 2 Article 107 10.56578/jisc030204 https://www.acadlore.com/article/JISC/2024_3_2/jisc030204 https://www.acadlore.com/article/JISC/2024_3_2/jisc030203 Regulatory bodies in electrical engineering mandate the installation of power factor (PF) improvement systems to elevate PF values to between 0.9 and 0.96. Compliance is enforced by regional or local utility companies through penal rates and incentives for PF values nearing unity. Traditional power factor correction (PFC) systems often utilize microprocessor-based controllers for switching capacitor banks, which can result in under- or over-compensation of reactive power. This study developed an adaptive neuro-fuzzy inference system (ANFIS) utilizing a Sugeno-Takagi inference model based on the sub-clustering method to address the limitations of sensitivity and response time observed in existing microcontroller-based PFC systems. The proposed neuro-fuzzy (NF) controller comprises a five-layered model with two inputs, i.e., kilowatt (KW) and kilovolt-ampere reactive (KVAR), and one output (PF). A 25-rule set performance of the developed program was achieved, with significant improvements observed after 50 epochs, culminating in an error rate of 0.050691 recorded post the second epoch. The results demonstrated that the developed controller exhibits higher sensitivity and faster response time compared to existing PF controllers. Consequently, the implementation of the proposed controller is recommended for optimizing the switching of capacitor banks, thereby enhancing PF in manufacturing industries characterized by variable load conditions. 06-29-2024 <![CDATA[ Regulatory bodies in electrical engineering mandate the installation of power factor (PF) improvement systems to elevate PF values to between 0.9 and 0.96. Compliance is enforced by regional or local utility companies through penal rates and incentives for PF values nearing unity. Traditional power factor correction (PFC) systems often utilize microprocessor-based controllers for switching capacitor banks, which can result in under- or over-compensation of reactive power. This study developed an adaptive neuro-fuzzy inference system (ANFIS) utilizing a Sugeno-Takagi inference model based on the sub-clustering method to address the limitations of sensitivity and response time observed in existing microcontroller-based PFC systems. The proposed neuro-fuzzy (NF) controller comprises a five-layered model with two inputs, i.e., kilowatt (KW) and kilovolt-ampere reactive (KVAR), and one output (PF). A 25-rule set performance of the developed program was achieved, with significant improvements observed after 50 epochs, culminating in an error rate of 0.050691 recorded post the second epoch. The results demonstrated that the developed controller exhibits higher sensitivity and faster response time compared to existing PF controllers. Consequently, the implementation of the proposed controller is recommended for optimizing the switching of capacitor banks, thereby enhancing PF in manufacturing industries characterized by variable load conditions. ]]> Neuro-Fuzzy Logic Controller for Switching Capacitor Banks in Power Factor Correction within the Manufacturing Industry olamide omolara olusanya gbenga mufutau adebajo ibrahim giwa kennedy okokpujie samuel adebayo daramola adenugba vincent akingunsoye doi: 10.56578/jisc030203 Journal of Intelligent Systems and Control 06-29-2024 Journal of Intelligent Systems and Control 06-29-2024 2024 3 2 Article 93 10.56578/jisc030203 https://www.acadlore.com/article/JISC/2024_3_2/jisc030203 https://www.acadlore.com/article/JISC/2024_3_2/jisc030202 This study evaluates the usability and effectiveness of a newly developed special education (SPED) campus navigation system designed for students with visual impairment (SVI) at the Federal College of Education (Special), Oyo, Oyo State, Nigeria. The primary objective was to assess the system's capability to facilitate self-navigation for SVI and identify challenges encountered in a campus environment. A mixed-methods approach, combining quantitative data from questionnaires and qualitative insights from interviews, was employed. Twenty SVI, selected through purposive sampling, participated in the study, using the system over a five-week period. The findings indicate significant improvements in the orientation and mobility of SVI, resulting in increased confidence in navigating the campus. Participants reported that the navigation system effectively aided in locating key areas, detecting obstacles, and ensuring safety. However, several critical challenges were identified, such as the system's voice being drowned out in noisy environments and the frequent need for battery recharging every five days. Participants suggested enhancements, including the incorporation of volume control to accommodate various environmental conditions and regular device charging to prevent battery depletion. These improvements are deemed essential for enhancing the system's reliability and usability for SVI. 06-29-2024 <![CDATA[ This study evaluates the usability and effectiveness of a newly developed special education (SPED) campus navigation system designed for students with visual impairment (SVI) at the Federal College of Education (Special), Oyo, Oyo State, Nigeria. The primary objective was to assess the system's capability to facilitate self-navigation for SVI and identify challenges encountered in a campus environment. A mixed-methods approach, combining quantitative data from questionnaires and qualitative insights from interviews, was employed. Twenty SVI, selected through purposive sampling, participated in the study, using the system over a five-week period. The findings indicate significant improvements in the orientation and mobility of SVI, resulting in increased confidence in navigating the campus. Participants reported that the navigation system effectively aided in locating key areas, detecting obstacles, and ensuring safety. However, several critical challenges were identified, such as the system's voice being drowned out in noisy environments and the frequent need for battery recharging every five days. Participants suggested enhancements, including the incorporation of volume control to accommodate various environmental conditions and regular device charging to prevent battery depletion. These improvements are deemed essential for enhancing the system's reliability and usability for SVI. ]]> Evaluating the Usability and Effectiveness of a Special Education Campus Navigation System for Students with Visual Impairment solomon babatunde olaleye benedictus adekunle adebiyi aminat abdulsalaam florence chika nwosu abosede olayinka adeyanju hassana mamman ambi clement omolayo doi: 10.56578/jisc030202 Journal of Intelligent Systems and Control 06-29-2024 Journal of Intelligent Systems and Control 06-29-2024 2024 3 2 Article 84 10.56578/jisc030202 https://www.acadlore.com/article/JISC/2024_3_2/jisc030202 https://www.acadlore.com/article/JISC/2024_3_2/jisc030201 In recent decades, the demand for electricity has continuously increased. Power generation facilities are predominantly situated at substantial distances from consumption centers, necessitating transmission over extensive, high-voltage lines. Such configurations lead to significant energy losses and diminished capacity and capability of transmission systems. Consequently, enhancements in transmission line performance have become a focal point for power system operators. The integration of the flexible alternating current transmission system (FACTS) technology has emerged as a pivotal solution, facilitating dynamic control over power flow and amplifying the existing capacity of power lines without the need for constructing new infrastructure. Among various FACTS devices, the static synchronous series compensator (SSSC) plays a crucial role by injecting variable capacitive or inductive reactance as required, thereby optimizing power flow and enhancing voltage stability. This review paper meticulously examines the functionality of different FACTS technologies, with a specific focus on the SSSC. Comparative analyses of transmission line performance, uncompensated, compensated through traditional series capacitors, and enhanced via SSSC, were conducted. The findings underscore the versatility of SSSC in reducing transmission losses and stabilizing network operations. This investigation not only details the operational benefits of SSSC but also explores its potential in addressing contemporary challenges in power transmission systems. 06-17-2024 <![CDATA[ In recent decades, the demand for electricity has continuously increased. Power generation facilities are predominantly situated at substantial distances from consumption centers, necessitating transmission over extensive, high-voltage lines. Such configurations lead to significant energy losses and diminished capacity and capability of transmission systems. Consequently, enhancements in transmission line performance have become a focal point for power system operators. The integration of the flexible alternating current transmission system (FACTS) technology has emerged as a pivotal solution, facilitating dynamic control over power flow and amplifying the existing capacity of power lines without the need for constructing new infrastructure. Among various FACTS devices, the static synchronous series compensator (SSSC) plays a crucial role by injecting variable capacitive or inductive reactance as required, thereby optimizing power flow and enhancing voltage stability. This review paper meticulously examines the functionality of different FACTS technologies, with a specific focus on the SSSC. Comparative analyses of transmission line performance, uncompensated, compensated through traditional series capacitors, and enhanced via SSSC, were conducted. The findings underscore the versatility of SSSC in reducing transmission losses and stabilizing network operations. This investigation not only details the operational benefits of SSSC but also explores its potential in addressing contemporary challenges in power transmission systems. ]]> Enhancing Power Transmission Efficiency Using Static Synchronous Series Compensators: A Comprehensive Review emad hussen sadiq laith a. mohammed harwan m. taha doi: 10.56578/jisc030201 Journal of Intelligent Systems and Control 06-17-2024 Journal of Intelligent Systems and Control 06-17-2024 2024 3 2 Article 71 10.56578/jisc030201 https://www.acadlore.com/article/JISC/2024_3_2/jisc030201 https://www.acadlore.com/article/JISC/2024_3_1/jisc030105 In the pursuit of optimizing automotive suspension systems, a semi-active suspension system (SASS) utilizing continuous skyhook control has been developed to enhance vehicle ride comfort and handling. This system is specifically engineered to mitigate vibrations stemming from high-frequency road excitations. Central to this advancement is the introduction of an electrohydraulic (EH) damper, which is uniquely characterized by solenoid valves capable of adjusting the orifice size to modify damping characteristics. By tuning the damping ratio, the system effectively minimizes the positional oscillations of the sprung mass in response to road irregularities. The dynamic behavior of this damper is comprehensively modeled through a boundary model approach, ensuring precise simulation and prediction of performance. A full-scale quarter-car test platform was constructed to evaluate the dynamic response and the efficacy of various control strategies implemented within the SASS. The performance assessments were conducted using MATLAB Simulink to simulate the behavior of the system under skyhook control algorithms, which aim to maintain the chassis’s vertical stability during disturbances. Comparative tests involving a single EH damper have demonstrated a high level of correlation with the simulated models, achieving a 95% agreement level. These findings underscore the capability of the SASS to surpass traditional hydraulic dampers in terms of performance, cost-efficiency, and versatility in testing applications. The insights garnered from this study not only validate the functionality of the proposed system but also contribute significantly to the body of knowledge in vehicle dynamics and control. This research provides a foundational framework for future exploration and potential implementation of advanced damping systems in the automotive industry. 03-30-2024 <![CDATA[ <p>In the pursuit of optimizing automotive suspension systems, a semi-active suspension system (SASS) utilizing continuous skyhook control has been developed to enhance vehicle ride comfort and handling. This system is specifically engineered to mitigate vibrations stemming from high-frequency road excitations. Central to this advancement is the introduction of an electrohydraulic (EH) damper, which is uniquely characterized by solenoid valves capable of adjusting the orifice size to modify damping characteristics. By tuning the damping ratio, the system effectively minimizes the positional oscillations of the sprung mass in response to road irregularities. The dynamic behavior of this damper is comprehensively modeled through a boundary model approach, ensuring precise simulation and prediction of performance. A full-scale quarter-car test platform was constructed to evaluate the dynamic response and the efficacy of various control strategies implemented within the SASS. The performance assessments were conducted using MATLAB Simulink to simulate the behavior of the system under skyhook control algorithms, which aim to maintain the chassis’s vertical stability during disturbances. Comparative tests involving a single EH damper have demonstrated a high level of correlation with the simulated models, achieving a 95% agreement level. These findings underscore the capability of the SASS to surpass traditional hydraulic dampers in terms of performance, cost-efficiency, and versatility in testing applications. The insights garnered from this study not only validate the functionality of the proposed system but also contribute significantly to the body of knowledge in vehicle dynamics and control. This research provides a foundational framework for future exploration and potential implementation of advanced damping systems in the automotive industry.</p> ]]> Enhancement of Vehicle Ride Quality Through Semi-Active Suspension: A Full-Scale Quarter-Car Test Rig Evaluation mohsin n. hamzah ammar s. merza bahaa-aldin r. abdullah doi: 10.56578/jisc030105 Journal of Intelligent Systems and Control 03-30-2024 Journal of Intelligent Systems and Control 03-30-2024 2024 3 1 Article 57 10.56578/jisc030105 https://www.acadlore.com/article/JISC/2024_3_1/jisc030105 https://www.acadlore.com/article/JISC/2024_3_1/jisc030104 In the era of low-carbon travel, maglev cars emerge as a high-speed, environmentally sustainable solution, leveraging their frictionless, smooth operation. This study introduces a nonlinear dynamic model for the longitudinal dynamics of maglev cars, constructed via a data-driven approach. A nonlinear model predictive control (NMPC) strategy, incorporating rotational speed constraints, is developed to address the inherent instability of the open-loop system. The dynamic relationship between the driving force and the rotational speeds of magnetic wheels was quantified using the least squares method (LSM) based on tests conducted across varied rotational speeds. A single-degree-of-freedom model, integrating stiffness and damping characteristics, was subsequently formulated to describe the longitudinal motion of the maglev car. The model’s validity was confirmed through comparison with experimental outputs under varying conditions. Further, the stiffness and damping coefficients were derived from experimental data, enhancing the model’s precision. Control simulations and real-world experiments under diverse operational conditions demonstrated the efficacy of the NMPC in ensuring robust longitudinal tracking. This investigation substantiates the NMPC approach as an effective control strategy for enhancing the stability and performance of maglev transportation systems. 03-30-2024 <![CDATA[ In the era of low-carbon travel, maglev cars emerge as a high-speed, environmentally sustainable solution, leveraging their frictionless, smooth operation. This study introduces a nonlinear dynamic model for the longitudinal dynamics of maglev cars, constructed via a data-driven approach. A nonlinear model predictive control (NMPC) strategy, incorporating rotational speed constraints, is developed to address the inherent instability of the open-loop system. The dynamic relationship between the driving force and the rotational speeds of magnetic wheels was quantified using the least squares method (LSM) based on tests conducted across varied rotational speeds. A single-degree-of-freedom model, integrating stiffness and damping characteristics, was subsequently formulated to describe the longitudinal motion of the maglev car. The model’s validity was confirmed through comparison with experimental outputs under varying conditions. Further, the stiffness and damping coefficients were derived from experimental data, enhancing the model’s precision. Control simulations and real-world experiments under diverse operational conditions demonstrated the efficacy of the NMPC in ensuring robust longitudinal tracking. This investigation substantiates the NMPC approach as an effective control strategy for enhancing the stability and performance of maglev transportation systems. ]]> Nonlinear Model Predictive Control for Longitudinal Tracking of Maglev Cars huiyang yi zhihao ke jinbin zou jiaheng shi zigang deng doi: 10.56578/jisc030104 Journal of Intelligent Systems and Control 03-30-2024 Journal of Intelligent Systems and Control 03-30-2024 2024 3 1 Article 42 10.56578/jisc030104 https://www.acadlore.com/article/JISC/2024_3_1/jisc030104 https://www.acadlore.com/article/JISC/2024_3_1/jisc030103 The quality of state estimation in uncertain systems exerts a significant impact on the performance of control systems. Within these uncertain systems, set-valued mappings introduce output uncertainties, complicating the design of observers. This study maps the output error of uncertain systems to the nonlinear terms of a framer , thereby extending the Luenberger framer. An interval observer design method for uncertain systems is proposed, leveraging monotone system theory to analyze the coherence of the error system. The effectiveness of the algorithm is validated through simulation examples. 03-30-2024 <![CDATA[ The quality of state estimation in uncertain systems exerts a significant impact on the performance of control systems. Within these uncertain systems, set-valued mappings introduce output uncertainties, complicating the design of observers. This study maps the output error of uncertain systems to the nonlinear terms of a framer , thereby extending the Luenberger framer. An interval observer design method for uncertain systems is proposed, leveraging monotone system theory to analyze the coherence of the error system. The effectiveness of the algorithm is validated through simulation examples. ]]> Enhanced Interval State Estimation for Uncertain Systems zhaoxia huang meng liu wanting dou dantong yang xinyu li jiayu zhang ying wang doi: 10.56578/jisc030103 Journal of Intelligent Systems and Control 03-30-2024 Journal of Intelligent Systems and Control 03-30-2024 2024 3 1 Article 33 10.56578/jisc030103 https://www.acadlore.com/article/JISC/2024_3_1/jisc030103 https://www.acadlore.com/article/JISC/2024_3_1/jisc030102 Unmanned Aerial Vehicles (UAVs), have recently sparked attention due to its versatility in a wide range of real-life uses. They require to be controlled so as to conduct different operations and widen their typical roles. This study proposes an optimal robust deadbeat controller for the roll angle motion of tail-sitter vertically take-off and land vehicles, taking into consideration the systems’ intrinsic sensitivity to outside influences and fluctuation of their dynamics. Primarily, several assumptions are used to develop an appropriate transfer function that reflects the system physical attributes. The suggested controller is then formed in two sections: the first section addresses the nominal system’s unstable dynamics, and the second element imposes the desired deadbeat performance and robustness. The control system variables are optimized using the creative and efficient Incomprehensible but Time-Intelligible Logics optimization technique, ensuring that the specified robustness demand is satisfied correctly. Finally, simulation is used to evaluate the developed controller effectiveness, revealing beneficial stability and performance indicators for both nominal and uncertain regulated system featuring uniform, bounded, and feasible closed-loop outputs. The control unit performs well, with a rising time of 0.0965 seconds, a settling time of 0.1134 seconds, and an overshoot of 0.167%. 03-30-2024 <![CDATA[ <p>Unmanned Aerial Vehicles (UAVs), have recently sparked attention due to its versatility in a wide range of real-life uses. They require to be controlled so as to conduct different operations and widen their typical roles. This study proposes an optimal robust deadbeat controller for the roll angle motion of tail-sitter vertically take-off and land vehicles, taking into consideration the systems’ intrinsic sensitivity to outside influences and fluctuation of their dynamics. Primarily, several assumptions are used to develop an appropriate transfer function that reflects the system physical attributes. The suggested controller is then formed in two sections: the first section addresses the nominal system’s unstable dynamics, and the second element imposes the desired deadbeat performance and robustness. The control system variables are optimized using the creative and efficient Incomprehensible but Time-Intelligible Logics optimization technique, ensuring that the specified robustness demand is satisfied correctly. Finally, simulation is used to evaluate the developed controller effectiveness, revealing beneficial stability and performance indicators for both nominal and uncertain regulated system featuring uniform, bounded, and feasible closed-loop outputs. The control unit performs well, with a rising time of 0.0965 seconds, a settling time of 0.1134 seconds, and an overshoot of 0.167%.</p> ]]> Design of an Optimized Robust Deadbeat Controller for Roll Motion in Tail-Sitter VTOL UAVs ali h. mhmood doi: 10.56578/jisc030102 Journal of Intelligent Systems and Control 03-30-2024 Journal of Intelligent Systems and Control 03-30-2024 2024 3 1 Article 21 10.56578/jisc030102 https://www.acadlore.com/article/JISC/2024_3_1/jisc030102 https://www.acadlore.com/article/JISC/2024_3_1/jisc030101 One significant benefit of the Maclaurin symmetric mean (MSM) is that it is a generalization of many extend operators and can consider the interrelationships among the multi-input arguments, such as multi-attributes or multi-experts in the multi-attribute group decision making (MAGDM). In the information fusion process, the Schweizer-Sklar T-norm (TN) and T-conorm (TCN), an important class of the TN and TCN, have more flexibility. We define SS operational rules of SFNs and extend SSTN, SSTCN to Spherical fuzzy values (SFVs) in order to fully utilize the advantages of SSTN, SSTCN, and MSM. Next, by combining the MSM with SS operational rules, we propose the spherical fuzzy Schweizer-Sklar weighted Maclaurin symmetric mean (SFSSWMSM) and spherical fuzzy Schweizer-Sklar Maclaurin symmetric mean (SFSSMSM) operators. This research examines their advantages and creates a novel approach based on these operators for particular MAGDM issues. Then, by comparing the suggested technique with current approaches in practical settings, its benefits and viability are demonstrated. Lastly, a few real-world examples are provided to demonstrate the applicability and benefits of the suggested approach in comparison to a few other approaches already in use. 03-30-2024 <![CDATA[ One significant benefit of the Maclaurin symmetric mean (MSM) is that it is a generalization of many extend operators and can consider the interrelationships among the multi-input arguments, such as multi-attributes or multi-experts in the multi-attribute group decision making (MAGDM). In the information fusion process, the Schweizer-Sklar T-norm (TN) and T-conorm (TCN), an important class of the TN and TCN, have more flexibility. We define SS operational rules of SFNs and extend SSTN, SSTCN to Spherical fuzzy values (SFVs) in order to fully utilize the advantages of SSTN, SSTCN, and MSM. Next, by combining the MSM with SS operational rules, we propose the spherical fuzzy Schweizer-Sklar weighted Maclaurin symmetric mean (SFSSWMSM) and spherical fuzzy Schweizer-Sklar Maclaurin symmetric mean (SFSSMSM) operators. This research examines their advantages and creates a novel approach based on these operators for particular MAGDM issues. Then, by comparing the suggested technique with current approaches in practical settings, its benefits and viability are demonstrated. Lastly, a few real-world examples are provided to demonstrate the applicability and benefits of the suggested approach in comparison to a few other approaches already in use. ]]> A Few Maclaurin Symmetric Mean Aggregation Operators for Spherical Fuzzy Numbers Based on Schweizer-Sklar Operations and Their Use in Artificial Intelligence mehwish sarfraz doi: 10.56578/jisc030101 Journal of Intelligent Systems and Control 03-30-2024 Journal of Intelligent Systems and Control 03-30-2024 2024 3 1 Article 1 10.56578/jisc030101 https://www.acadlore.com/article/JISC/2024_3_1/jisc030101 https://www.acadlore.com/article/JISC/2023_2_4/jisc020405 This study presents the two-stage cubature Kalman filter (TSCKF), which is a sophisticated technique designed to address the issue of variations in system models in real-life scenarios, and utilises nonlinear two-stage transformations to reorganise covariance matrices into a block-diagonal structure, effectively overcoming the limitations of conventional augmented methods. This technique effectively eliminates the need to calculate the cross-covariance between state variables and biases. This leads to a substantial reduction in computational load and facilitates seamless operation of the filter. The TSCKF design is underpinned by a robust theoretical framework, which ensures optimal computational efficiency while also ensuring precise estimations. This work demonstrates the mathematical equivalence between the TSCKF and the standard cubature Kalman filter (CKF) by utilising updated information equivalent transformations, and empirically verifies the equivalence through trajectory tracking experiments conducted on two-wheeled robotic systems subjected to random perturbations, thus affirming the greater accuracy and dependability of the TSCKF in tracking scenarios. Moreover, comparison evaluations offer further proof of the same performance between both methodologies. This study introduces a highly efficient approach in the domain of nonlinear systems and provides a dependable remedy for scenarios where traditional filtering procedures may be inadequate due to deficiencies in the system model. 12-30-2023 <![CDATA[ This study presents the two-stage cubature Kalman filter (TSCKF), which is a sophisticated technique designed to address the issue of variations in system models in real-life scenarios, and utilises nonlinear two-stage transformations to reorganise covariance matrices into a block-diagonal structure, effectively overcoming the limitations of conventional augmented methods. This technique effectively eliminates the need to calculate the cross-covariance between state variables and biases. This leads to a substantial reduction in computational load and facilitates seamless operation of the filter. The TSCKF design is underpinned by a robust theoretical framework, which ensures optimal computational efficiency while also ensuring precise estimations. This work demonstrates the mathematical equivalence between the TSCKF and the standard cubature Kalman filter (CKF) by utilising updated information equivalent transformations, and empirically verifies the equivalence through trajectory tracking experiments conducted on two-wheeled robotic systems subjected to random perturbations, thus affirming the greater accuracy and dependability of the TSCKF in tracking scenarios. Moreover, comparison evaluations offer further proof of the same performance between both methodologies. This study introduces a highly efficient approach in the domain of nonlinear systems and provides a dependable remedy for scenarios where traditional filtering procedures may be inadequate due to deficiencies in the system model. ]]> Target Tracking Algorithm Using Two-Stage Cubature Kalman Filter lu zhang ashish bagwari gang huang doi: 10.56578/jisc020405 Journal of Intelligent Systems and Control 12-30-2023 Journal of Intelligent Systems and Control 12-30-2023 2023 2 4 Article 230 10.56578/jisc020405 https://www.acadlore.com/article/JISC/2023_2_4/jisc020405 https://www.acadlore.com/article/JISC/2023_2_4/jisc020404 In the field of industrial motor control, the inherent design complexity and operational challenge of dual star induction motor (DSIM) have made it a focus of research for many scholars. This study attempts to innovatively propose a refined control approach for DSIM, by deploying two pulse width modulation (PWM) voltage sources combining with indirect field-oriented control (IFOC). Core of our innovation is the integration of a super twisting algorithm (STA) controller, which is a strategy specifically designed to enhance the motor's speed control capability. The paper introduced the technical details of DSIM, with the focus placed on the distinctive configuration of two isolated neutral three-phase windings, set apart by a 30-degree electrical phase shift. Such design has posed certain control challenges, and the STA approach has skillfully addressed these challenges. With the help of Matlab/Simulink simulations, the efficacy of STA controller is evaluated and compared with the common Proportional-Integral (PI) controller, and the simulation results are indicative of the STA controller's superiority, showing a significant improvement in reducing torque ripples and stator current fluctuations. The analysis given in the paper quantifies the improvement, showing substantial reductions in steady-state error and response time, as well as an enhanced disturbance rejection capability. These findings are instrumental in showcasing the STA controller's comparative advantage. Concludingly, the adoption of the STA-based control methodology in DSIM applications not only fosters enhanced speed control and efficiency but also holds the promise of broad applicability across various industrial scenarios. This research, therefore, marks a pivotal advancement in the field of DSIM control, potentially revolutionizing its application in diverse industrial settings. The consistency in the use of professional terminology throughout the paper ensures a coherent and comprehensive understanding of the subject matter. 12-30-2023 <![CDATA[ In the field of industrial motor control, the inherent design complexity and operational challenge of dual star induction motor (DSIM) have made it a focus of research for many scholars. This study attempts to innovatively propose a refined control approach for DSIM, by deploying two pulse width modulation (PWM) voltage sources combining with indirect field-oriented control (IFOC). Core of our innovation is the integration of a super twisting algorithm (STA) controller, which is a strategy specifically designed to enhance the motor's speed control capability. The paper introduced the technical details of DSIM, with the focus placed on the distinctive configuration of two isolated neutral three-phase windings, set apart by a 30-degree electrical phase shift. Such design has posed certain control challenges, and the STA approach has skillfully addressed these challenges. With the help of Matlab/Simulink simulations, the efficacy of STA controller is evaluated and compared with the common Proportional-Integral (PI) controller, and the simulation results are indicative of the STA controller's superiority, showing a significant improvement in reducing torque ripples and stator current fluctuations. The analysis given in the paper quantifies the improvement, showing substantial reductions in steady-state error and response time, as well as an enhanced disturbance rejection capability. These findings are instrumental in showcasing the STA controller's comparative advantage. Concludingly, the adoption of the STA-based control methodology in DSIM applications not only fosters enhanced speed control and efficiency but also holds the promise of broad applicability across various industrial scenarios. This research, therefore, marks a pivotal advancement in the field of DSIM control, potentially revolutionizing its application in diverse industrial settings. The consistency in the use of professional terminology throughout the paper ensures a coherent and comprehensive understanding of the subject matter. ]]> Enhanced Control of Dual Star Induction Motor via Super Twisting Algorithm: A Comparative Analysis with Classical PI Controllers es-saadi terfia sofiane mendaci salah eddine rezgui hamza gasmi walid kantas doi: 10.56578/jisc020404 Journal of Intelligent Systems and Control 12-30-2023 Journal of Intelligent Systems and Control 12-30-2023 2023 2 4 Article 220 10.56578/jisc020404 https://www.acadlore.com/article/JISC/2023_2_4/jisc020404 https://www.acadlore.com/article/JISC/2023_2_4/jisc020403 LLC resonant converters own high power efficiency and density, and are widely used in electric vehicles, intelligent and communication power sources, and other fields. The converters cannot obtain accurate mathematical models and their nonlinear characteristics are complex. Therefore, traditional proportional-integral (PI) control cannot achieve control effect well. The dynamic matrix control (DMC) strategy was applied to the converter model, aiming to improve the system’s dynamic response and reduce overshoot. In addition, the DMC algorithm was used in this study to achieve precise system control. The algorithm is robust, and can improve the system’s stability and reliability. At the same time, the system can be flexibly controlled through parameter adjustment. Furthermore, a voltage prediction closed-loop controller was designed to enhance the system’s dynamic performance. In addition, a simulation model was built based on this to verify the feasibility and effectiveness of the scheme. The simulation results showed that the DMC algorithm suppressed overshoot and improved dynamic response effectively. 12-27-2023 <![CDATA[ LLC resonant converters own high power efficiency and density, and are widely used in electric vehicles, intelligent and communication power sources, and other fields. The converters cannot obtain accurate mathematical models and their nonlinear characteristics are complex. Therefore, traditional proportional-integral (PI) control cannot achieve control effect well. The dynamic matrix control (DMC) strategy was applied to the converter model, aiming to improve the system’s dynamic response and reduce overshoot. In addition, the DMC algorithm was used in this study to achieve precise system control. The algorithm is robust, and can improve the system’s stability and reliability. At the same time, the system can be flexibly controlled through parameter adjustment. Furthermore, a voltage prediction closed-loop controller was designed to enhance the system’s dynamic performance. In addition, a simulation model was built based on this to verify the feasibility and effectiveness of the scheme. The simulation results showed that the DMC algorithm suppressed overshoot and improved dynamic response effectively. ]]> Control of DMC-Based LLC Resonant Converters xixi han zhibo lin keqi kang xiaopei zhu doi: 10.56578/jisc020403 Journal of Intelligent Systems and Control 12-27-2023 Journal of Intelligent Systems and Control 12-27-2023 2023 2 4 Article 209 10.56578/jisc020403 https://www.acadlore.com/article/JISC/2023_2_4/jisc020403 https://www.acadlore.com/article/JISC/2023_2_4/jisc020402 This study explores dynamic simulation and integrated control in a space robotic arm system characterized by a fully-flexible arm and an elastic base. The elastic base is modeled as a lightweight spring, and the modal shapes of a simply-supported beam are selected via the assumed mode method to represent the bending vibrations of the flexible arm. Dynamic equations for the system are formulated by integrating Lagrangian mechanics with momentum conservation principles. The approach involves reducing the system into two lower-order subsystems using a dual-time-scale singular perturbation method. The first subsystem, exhibiting slow variation, accounts for the joint's rigid motion, while the second, fast-varying subsystem addresses the vibrations of the base and arm. Estimation of joint velocities is conducted through a Luenberger observer, complemented by the use of an Radial Basis Function (RBF) neural network to approximate parameter uncertainties within the system. This facilitates the control of rigid motion in the slow-varying subsystem. Subsequently, the fast-varying subsystem's vibration is actively controlled based on linear system optimal control theory. Numerical simulations validate the integrated control approach's effectiveness in managing both motion and vibration, demonstrating its potential in enhancing the operational precision and stability of space robot systems. 12-05-2023 <![CDATA[ This study explores dynamic simulation and integrated control in a space robotic arm system characterized by a fully-flexible arm and an elastic base. The elastic base is modeled as a lightweight spring, and the modal shapes of a simply-supported beam are selected via the assumed mode method to represent the bending vibrations of the flexible arm. Dynamic equations for the system are formulated by integrating Lagrangian mechanics with momentum conservation principles. The approach involves reducing the system into two lower-order subsystems using a dual-time-scale singular perturbation method. The first subsystem, exhibiting slow variation, accounts for the joint's rigid motion, while the second, fast-varying subsystem addresses the vibrations of the base and arm. Estimation of joint velocities is conducted through a Luenberger observer, complemented by the use of an Radial Basis Function (RBF) neural network to approximate parameter uncertainties within the system. This facilitates the control of rigid motion in the slow-varying subsystem. Subsequently, the fast-varying subsystem's vibration is actively controlled based on linear system optimal control theory. Numerical simulations validate the integrated control approach's effectiveness in managing both motion and vibration, demonstrating its potential in enhancing the operational precision and stability of space robot systems. ]]> Neural Network-Based Control and Active Vibration Mitigation in a Fully-Flexible Arm Space Robot under Elastic Base Influence: A Luenberger Observer Approach lijiao zhang xiaoyan yu doi: 10.56578/jisc020402 Journal of Intelligent Systems and Control 12-05-2023 Journal of Intelligent Systems and Control 12-05-2023 2023 2 4 Article 197 10.56578/jisc020402 https://www.acadlore.com/article/JISC/2023_2_4/jisc020402 https://www.acadlore.com/article/JISC/2023_2_4/jisc020401 This study presents a comprehensive evaluation of linear and non-linear control systems, specifically Proportion Integration Differentiation (PID) and fuzzy logic controllers, in the context of position control within double-link robotic manipulators. The effectiveness of these controllers was rigorously assessed in a simulated environment, utilizing MATLAB Simulink for the simulation and SOLIDWORKS for the model design. The PID controller, characterized by its Kp, Ki, and Kd components, was implemented both in the simulation and on the hardware. However, due to the constraints of the microcontroller's RAM and processor, which facilitate the hardware's connection with MATLAB, the application of the Fuzzy Logic concept to hardware was not feasible. In the simulated environment, the fuzzy logic controller demonstrated superior stability in comparison to the PID controller, evidenced by a lower settling time (1.0 seconds) and overshoot (2%). In contrast, the PID controller exhibited a settling time of 0.2 seconds and an overshoot of 32%. Additionally, the fuzzy logic controller showcased a 44% reduction in steady-state error relative to the PID controller. When applied to hardware, the PID controller maintained stable results, achieving a settling time of 0.6 seconds and an overshoot of 2%. The steady-state errors for Link 1 and Link 2 were recorded as 3.6° and 1.4°, respectively. The findings highlight the fuzzy logic controller's enhanced stability, rendering it more suitable for ensuring the accuracy and protection of the manipulator system. As a non-linear controller, the fuzzy logic controller efficiently addresses various potential errors through its intelligent control mechanism, which is embedded in its fuzzy rules. Conversely, the PID controller, a linear controller, responds rapidly but may lack flexibility in complex scenarios due to its inherent linearity. This study underscores the importance of selecting an appropriate controller based on the specific requirements of robotic manipulator systems, with a focus on achieving optimal performance and stability. 11-28-2023 <![CDATA[ <p>This study presents a comprehensive evaluation of linear and non-linear control systems, specifically Proportion Integration Differentiation (PID) and fuzzy logic controllers, in the context of position control within double-link robotic manipulators. The effectiveness of these controllers was rigorously assessed in a simulated environment, utilizing MATLAB Simulink for the simulation and SOLIDWORKS for the model design. The PID controller, characterized by its<em> Kp, Ki,</em> and <em>Kd</em> components, was implemented both in the simulation and on the hardware. However, due to the constraints of the microcontroller's RAM and processor, which facilitate the hardware's connection with MATLAB, the application of the Fuzzy Logic concept to hardware was not feasible. In the simulated environment, the fuzzy logic controller demonstrated superior stability in comparison to the PID controller, evidenced by a lower settling time (1.0 seconds) and overshoot (2%). In contrast, the PID controller exhibited a settling time of 0.2 seconds and an overshoot of 32%. Additionally, the fuzzy logic controller showcased a 44% reduction in steady-state error relative to the PID controller. When applied to hardware, the PID controller maintained stable results, achieving a settling time of 0.6 seconds and an overshoot of 2%. The steady-state errors for Link 1 and Link 2 were recorded as 3.6° and 1.4°, respectively. The findings highlight the fuzzy logic controller's enhanced stability, rendering it more suitable for ensuring the accuracy and protection of the manipulator system. As a non-linear controller, the fuzzy logic controller efficiently addresses various potential errors through its intelligent control mechanism, which is embedded in its fuzzy rules. Conversely, the PID controller, a linear controller, responds rapidly but may lack flexibility in complex scenarios due to its inherent linearity. This study underscores the importance of selecting an appropriate controller based on the specific requirements of robotic manipulator systems, with a focus on achieving optimal performance and stability.</p> ]]> Comparative Analysis of PID and Fuzzy Logic Controllers for Position Control in Double-Link Robotic Manipulators nor maniha abdul ghani aqib othman azrul azim abdullah hashim ahmas nor kasrudin nasir doi: 10.56578/jisc020401 Journal of Intelligent Systems and Control 11-28-2023 Journal of Intelligent Systems and Control 11-28-2023 2023 2 4 Article 183 10.56578/jisc020401 https://www.acadlore.com/article/JISC/2023_2_4/jisc020401 https://www.acadlore.com/article/JISC/2023_2_3/jisc020305 In this investigation, the robust H$\infty$ control of nonlinear electric vehicles (EVs), powered by permanent magnet synchronous motors (PMSM), was examined. Emphasis was placed on enhancing the accuracy and robustness of the vehicle speed regulation by incorporating a meticulous H$\infty$ method, supplemented by the proficient integration of Linear Matrix Inequality (LMI). A solution predicated on the LMI approach was devised, encompassing two distinct H$\infty$ controllers for both current and speed control. Subsequent to an extensive analysis of the mathematical and control model of the EV, weighting functions were judiciously selected to optimize stability and performance. The proposed methodology offers significant advancements in the domain of EV control strategies and proffers insights into the application of robust control methods. Through comprehensive simulations, the effectiveness of the outlined method was validated, revealing impeccable speed control and ensuring steadfast performance when applied to the dynamic model of an EV equipped with a PMSM motor. This research elucidates the progressive strides made in the realm of EV control tactics and offers profound understandings of robust control methodologies. 09-27-2023 <![CDATA[ <p>In this investigation, the robust H$\infty$ control of nonlinear electric vehicles (EVs), powered by permanent magnet synchronous motors (PMSM), was examined. Emphasis was placed on enhancing the accuracy and robustness of the vehicle speed regulation by incorporating a meticulous H$\infty$ method, supplemented by the proficient integration of Linear Matrix Inequality (LMI). A solution predicated on the LMI approach was devised, encompassing two distinct H$\infty$ controllers for both current and speed control. Subsequent to an extensive analysis of the mathematical and control model of the EV, weighting functions were judiciously selected to optimize stability and performance. The proposed methodology offers significant advancements in the domain of EV control strategies and proffers insights into the application of robust control methods. Through comprehensive simulations, the effectiveness of the outlined method was validated, revealing impeccable speed control and ensuring steadfast performance when applied to the dynamic model of an EV equipped with a PMSM motor. This research elucidates the progressive strides made in the realm of EV control tactics and offers profound understandings of robust control methodologies.</p> ]]> Robust Speed Control in Nonlinear Electric Vehicles Using H-Infinity Control and the LMI Approach farid oudjama abdelmadjid boumediene khayreddine saidi djamila boubekeur doi: 10.56578/jisc020305 Journal of Intelligent Systems and Control 09-27-2023 Journal of Intelligent Systems and Control 09-27-2023 2023 2 3 Article 170 10.56578/jisc020305 https://www.acadlore.com/article/JISC/2023_2_3/jisc020305 https://www.acadlore.com/article/JISC/2023_2_3/jisc020304 Robotic Process Automation (RPA), employing software robots or bots, has emerged as a pivotal technological advancement, automating repetitive, rule-based tasks within business operations. This leads to enhanced operational efficiency and substantial cost reductions. In this systematic review, information was extracted from 62 pertinent research articles on RPA published between 2016 and 2022. The findings elucidate the fundamental principles of RPA, predominant trends, and leading RPA frameworks, alongside their optimal industry applications. Moreover, the necessary procedural steps for RPA implementation in industries are delineated. The objectives of this study encompass highlighting contemporary RPA research directions and evaluating its potential in streamlining diverse business processes. 09-10-2023 <![CDATA[ <p>Robotic Process Automation (RPA), employing software robots or bots, has emerged as a pivotal technological advancement, automating repetitive, rule-based tasks within business operations. This leads to enhanced operational efficiency and substantial cost reductions. In this systematic review, information was extracted from 62 pertinent research articles on RPA published between 2016 and 2022. The findings elucidate the fundamental principles of RPA, predominant trends, and leading RPA frameworks, alongside their optimal industry applications. Moreover, the necessary procedural steps for RPA implementation in industries are delineated. The objectives of this study encompass highlighting contemporary RPA research directions and evaluating its potential in streamlining diverse business processes.</p> ]]> A Systematic Review of Robotic Process Automation in Business Operations: Contemporary Trends and Insights vivek bhardwaj doi: 10.56578/jisc020304 Journal of Intelligent Systems and Control 09-10-2023 Journal of Intelligent Systems and Control 09-10-2023 2023 2 3 Article 153 10.56578/jisc020304 https://www.acadlore.com/article/JISC/2023_2_3/jisc020304 https://www.acadlore.com/article/JISC/2023_2_3/jisc020303 In this study, the challenges of load variations, input voltage fluctuations, and reference voltage deviations for a DC-DC buck converter system are addressed. A composite voltage controller, founded on a model predictive control (MPC) integrated with a reduced-order state observer (RESO), is introduced to ameliorate the tracking performances of such converters. Disturbances, both matched and mismatched, are conceptualized as total disturbances within an innovatively proposed error tracking model. Subsequently, a RESO is meticulously developed to estimate and attenuate these disturbances. In parallel, an MPC is crafted to ensure enhanced system robustness and superior steady-state performances. Comparative simulations indicate that this innovative composite controller exhibits a rapid settling time and smoother response curve compared to traditional MPC. Furthermore, it is observed that when exposed to disturbances, the proposed methodology demonstrates heightened disturbance rejection capabilities, accelerated voltage tracking, and improved steady-state performance. 08-24-2023 <![CDATA[ <p>In this study, the challenges of load variations, input voltage fluctuations, and reference voltage deviations for a DC-DC buck converter system are addressed. A composite voltage controller, founded on a model predictive control (MPC) integrated with a reduced-order state observer (RESO), is introduced to ameliorate the tracking performances of such converters. Disturbances, both matched and mismatched, are conceptualized as total disturbances within an innovatively proposed error tracking model. Subsequently, a RESO is meticulously developed to estimate and attenuate these disturbances. In parallel, an MPC is crafted to ensure enhanced system robustness and superior steady-state performances. Comparative simulations indicate that this innovative composite controller exhibits a rapid settling time and smoother response curve compared to traditional MPC. Furthermore, it is observed that when exposed to disturbances, the proposed methodology demonstrates heightened disturbance rejection capabilities, accelerated voltage tracking, and improved steady-state performance.</p> ]]> Enhanced Tracking of DC-DC Buck Converter Systems Using Reduced-Order Extended State Observer-Based Model Predictive Control bozhao wang shengquan li shiqi kan juan li doi: 10.56578/jisc020303 Journal of Intelligent Systems and Control 08-24-2023 Journal of Intelligent Systems and Control 08-24-2023 2023 2 3 Article 143 10.56578/jisc020303 https://www.acadlore.com/article/JISC/2023_2_3/jisc020303 https://www.acadlore.com/article/JISC/2023_2_3/jisc020302 Sign language plays a crucial role in communication for individuals with speech or hearing difficulties. However, the lack of a comprehensive Indian Sign Language (ISL) corpus impedes the development of text-to-ISL conversion systems. This study proposes a specific deep learning-based sign language detection system tailored specifically for Indian Sign Language (ISL). The proposed system utilizes Long Short-Term Memory (LSTM) networks to detect and recognize actions from dynamic ISL gestures captured in videos. Initially, the system employs computer vision algorithms to extract relevant features and representations from the input gestures. Subsequently, an LSTM-based deep learning architecture is employed to capture the temporal dependencies and patterns within the gestures. LSTM models excel in sequential data processing, making them well-suited for analyzing the dynamic nature of sign language gestures. To assess the effectiveness of the proposed system, extensive experimentation and evaluation were conducted. A customized dataset was curated, encompassing a diverse range of ISL sign language actions. This dataset was created by collecting video recordings of native ISL users performing various actions, ensuring comprehensive coverage of gestures and expressions. These videos were meticulously annotated and labelled with corresponding textual representations of the gestures. The dataset was then split into training and testing sets to train the LSTM-based model and evaluate its performance. The proposed system yielded promising results during the validation process, achieving a training accuracy of 96% and a test accuracy of 87% for ISL recognition. These results outperformed previous approaches in the field. The system's ability to effectively detect and recognize actions from dynamic ISL gestures, facilitated by the deep learning-based approach utilizing LSTM networks, demonstrates the potential for more accurate and robust sign language recognition systems. However, it is important to acknowledge the limitations of the system. Currently, the system's primary focus is on recognizing individual words rather than full sentences, indicating the need for further research to enhance sentence-level interpretations. Additionally, variations in lighting conditions, camera angles, and hand orientations can potentially impact the system's accuracy, particularly in the context of ISL. 07-19-2023 <![CDATA[ <p>Sign language plays a crucial role in communication for individuals with speech or hearing difficulties. However, the lack of a comprehensive Indian Sign Language (ISL) corpus impedes the development of text-to-ISL conversion systems. This study proposes a specific deep learning-based sign language detection system tailored specifically for Indian Sign Language (ISL). The proposed system utilizes Long Short-Term Memory (LSTM) networks to detect and recognize actions from dynamic ISL gestures captured in videos. Initially, the system employs computer vision algorithms to extract relevant features and representations from the input gestures. Subsequently, an LSTM-based deep learning architecture is employed to capture the temporal dependencies and patterns within the gestures. LSTM models excel in sequential data processing, making them well-suited for analyzing the dynamic nature of sign language gestures. To assess the effectiveness of the proposed system, extensive experimentation and evaluation were conducted. A customized dataset was curated, encompassing a diverse range of ISL sign language actions. This dataset was created by collecting video recordings of native ISL users performing various actions, ensuring comprehensive coverage of gestures and expressions. These videos were meticulously annotated and labelled with corresponding textual representations of the gestures. The dataset was then split into training and testing sets to train the LSTM-based model and evaluate its performance. The proposed system yielded promising results during the validation process, achieving a training accuracy of 96% and a test accuracy of 87% for ISL recognition. These results outperformed previous approaches in the field. The system's ability to effectively detect and recognize actions from dynamic ISL gestures, facilitated by the deep learning-based approach utilizing LSTM networks, demonstrates the potential for more accurate and robust sign language recognition systems. However, it is important to acknowledge the limitations of the system. Currently, the system's primary focus is on recognizing individual words rather than full sentences, indicating the need for further research to enhance sentence-level interpretations. Additionally, variations in lighting conditions, camera angles, and hand orientations can potentially impact the system's accuracy, particularly in the context of ISL.</p> ]]> Detection and Interpretation of Indian Sign Language Using LSTM Networks piyusha vyavahare sanket dhawale priyanka takale vikrant koli bhavana kanawade shraddha khonde doi: 10.56578/jisc020302 Journal of Intelligent Systems and Control 07-19-2023 Journal of Intelligent Systems and Control 07-19-2023 2023 2 3 Article 132 10.56578/jisc020302 https://www.acadlore.com/article/JISC/2023_2_3/jisc020302 https://www.acadlore.com/article/JISC/2023_2_3/jisc020301 A significant surge in the installation of Vertical Axis Wind Turbines (VAWTs) in areas of spatial constraints and fluctuating wind directions has been observed, attributable to the omission of a yaw mechanism, which otherwise would require orientation towards wind direction. Among VAWTs, the Savonius variant, characterized by an S-shaped rotor, assumes a particular interest due to its operational advantages in the drag-based regime and its self-starting capability. Given their ability to generate electricity under low-wind-speed conditions, these turbines are markedly suited for urban locales. This investigation deploys Computational Fluid Dynamics (CFD) analysis, utilizing ANSYS CFX software, on VAWTs of varying blade heights, facilitating the measurement of torque generation under distinct air velocities. The wind turbine models for this analysis were designed using Creo software. Concurrently, an exploration into the feasibility of VAWTs for hydrogen production through electrolysis is undertaken using analytical methods. Results highlight the substantial influence of turbine height on power generation, which subsequently has direct repercussions on hydrogen production efficiency via the electrolyzer. A 600 mm height VAWT yielded the maximum hydrogen production of 1.05 kg, whereas an 800 mm height VAWT resulted in the minimum production of 0.339 kg. The research findings underscore the potential of VAWTs in hydrogen generation, emphasizing the critical role of wind turbine design optimization in augmenting power generation and, thus, hydrogen production. 07-19-2023 <![CDATA[ <p>A significant surge in the installation of Vertical Axis Wind Turbines (VAWTs) in areas of spatial constraints and fluctuating wind directions has been observed, attributable to the omission of a yaw mechanism, which otherwise would require orientation towards wind direction. Among VAWTs, the Savonius variant, characterized by an S-shaped rotor, assumes a particular interest due to its operational advantages in the drag-based regime and its self-starting capability. Given their ability to generate electricity under low-wind-speed conditions, these turbines are markedly suited for urban locales. This investigation deploys Computational Fluid Dynamics (CFD) analysis, utilizing ANSYS CFX software, on VAWTs of varying blade heights, facilitating the measurement of torque generation under distinct air velocities. The wind turbine models for this analysis were designed using Creo software. Concurrently, an exploration into the feasibility of VAWTs for hydrogen production through electrolysis is undertaken using analytical methods. Results highlight the substantial influence of turbine height on power generation, which subsequently has direct repercussions on hydrogen production efficiency via the electrolyzer. A 600 mm height VAWT yielded the maximum hydrogen production of 1.05 kg, whereas an 800 mm height VAWT resulted in the minimum production of 0.339 kg. The research findings underscore the potential of VAWTs in hydrogen generation, emphasizing the critical role of wind turbine design optimization in augmenting power generation and, thus, hydrogen production.</p> ]]> Computational Fluid Dynamics Analysis of Vertical Axis Wind Turbine Heights for Enhanced Hydrogen Production in Urban Environments mthembu linda abhishek agarwal pramod sinha doi: 10.56578/jisc020301 Journal of Intelligent Systems and Control 07-19-2023 Journal of Intelligent Systems and Control 07-19-2023 2023 2 3 Article 123 10.56578/jisc020301 https://www.acadlore.com/article/JISC/2023_2_3/jisc020301 https://www.acadlore.com/article/JISC/2023_2_2/jisc020205 This study introduces a new ten-term 5-D hyperchaotic system, derived from the 3-D Sprott C system. The proposed system has coexisting two attractors: the self-excited and hidden attractors. This system exhibits a rich array of characteristics, taking inspiration from various forms of equilibrium points, stable focus-nodes, saddle-focus, and non-hyperbolic unstable points. These features are shown to be dependent on parameter adjustments. The coexistence of chaotic and hyperchaotic attractors within a 5-D system coupled with three types of equilibrium points is an intriguing phenomenon. A spectrum of numerical methodologies, including phase portraits, computation of Lyapunov exponent, estimation of Lyapunov dimension, and multistability analysis, have been employed to effectively illustrate the diverse attractors. The stability theory is utilized for investigating the synchronization problem, a topic that is elucidated in depth. An assortment of dynamical behavior, such as hyperchaotic, hyperchaotic with 2-tours, chaotic, and chaotic with 2-tours, is recognized. Validation of the primary findings is conducted via theoretical and numerical simulations, fortifying the theoretical conclusions, with numerical simulations executed using MATLAB2021. 06-29-2023 <![CDATA[ <p>This study introduces a new ten-term 5-D hyperchaotic system, derived from the 3-D Sprott C system. The proposed system has coexisting two attractors: the self-excited and hidden attractors. This system exhibits a rich array of characteristics, taking inspiration from various forms of equilibrium points, stable focus-nodes, saddle-focus, and non-hyperbolic unstable points. These features are shown to be dependent on parameter adjustments. The coexistence of chaotic and hyperchaotic attractors within a 5-D system coupled with three types of equilibrium points is an intriguing phenomenon. A spectrum of numerical methodologies, including phase portraits, computation of Lyapunov exponent, estimation of Lyapunov dimension, and multistability analysis, have been employed to effectively illustrate the diverse attractors. The stability theory is utilized for investigating the synchronization problem, a topic that is elucidated in depth. An assortment of dynamical behavior, such as hyperchaotic, hyperchaotic with 2-tours, chaotic, and chaotic with 2-tours, is recognized. Validation of the primary findings is conducted via theoretical and numerical simulations, fortifying the theoretical conclusions, with numerical simulations executed using MATLAB2021.</p> ]]> New 5D Hyperchaotic System Derived from the Sprott C System: Properties and Anti Synchronization saad fawzi al-azzawi anmar m. hasan doi: 10.56578/jisc020205 Journal of Intelligent Systems and Control 06-29-2023 Journal of Intelligent Systems and Control 06-29-2023 2023 2 2 Article 110 10.56578/jisc020205 https://www.acadlore.com/article/JISC/2023_2_2/jisc020205 https://www.acadlore.com/article/JISC/2023_2_2/jisc020204 Unmanned Aerial Vehicles (UAVs), in the form of ornithopters, which emulate avian flight through wing flapping, have been the focus of this investigation. The remarkable maneuverability of birds and insects, often lacking in conventional aircraft, is harnessed to advance the control and stability of flapping wing flight. The need for such exploration is driven by the potential benefits to both scientific inquiry and societal applications. This investigation tackles the task of tailoring the ornithopter's design and component choice to cater to performance expectations derived from the flight attributes of birds, such as superior maneuverability, agility, low-speed flight capabilities, and high propulsive efficiency. The primary goal is to ensure a sustained airborne state through the generation of lift equivalent to the ornithopter's weight. Commonly available materials have been employed in the construction of the ornithopter. SolidWorks flow simulator was utilized to simulate aerodynamics. A 1000mm length of the wing was subjected to a 3m/s air stream at a 5-degree angle of attack for the simulation. The simulated result, which represents a 2kg ornithopter, exhibited a lift force of 0.8N and a drag force of 0.2N. Further simulations were conducted at varying attack angles (from 0 to 35 degrees) to gauge the range of lift and drag coefficients. The investigation concludes that the constructed ornithopter should generate an upward thrust of 2.7N at a speed of 5m/s, even without wing flapping, ensuring controlled and stable flight. 06-29-2023 <![CDATA[ <p>Unmanned Aerial Vehicles (UAVs), in the form of ornithopters, which emulate avian flight through wing flapping, have been the focus of this investigation. The remarkable maneuverability of birds and insects, often lacking in conventional aircraft, is harnessed to advance the control and stability of flapping wing flight. The need for such exploration is driven by the potential benefits to both scientific inquiry and societal applications. This investigation tackles the task of tailoring the ornithopter's design and component choice to cater to performance expectations derived from the flight attributes of birds, such as superior maneuverability, agility, low-speed flight capabilities, and high propulsive efficiency. The primary goal is to ensure a sustained airborne state through the generation of lift equivalent to the ornithopter's weight. Commonly available materials have been employed in the construction of the ornithopter. SolidWorks flow simulator was utilized to simulate aerodynamics. A 1000mm length of the wing was subjected to a 3m/s air stream at a 5-degree angle of attack for the simulation. The simulated result, which represents a 2kg ornithopter, exhibited a lift force of 0.8N and a drag force of 0.2N. Further simulations were conducted at varying attack angles (from 0 to 35 degrees) to gauge the range of lift and drag coefficients. The investigation concludes that the constructed ornithopter should generate an upward thrust of 2.7N at a speed of 5m/s, even without wing flapping, ensuring controlled and stable flight.</p> ]]> Advancements in the Design and Automation of Biomimetic Ornithopters: An Investigation into Flapping-Wing Flight Control adedotun adetunla bernard adaramola habeebullah abdulkadir doi: 10.56578/jisc020204 Journal of Intelligent Systems and Control 06-29-2023 Journal of Intelligent Systems and Control 06-29-2023 2023 2 2 Article 99 10.56578/jisc020204 https://www.acadlore.com/article/JISC/2023_2_2/jisc020204 https://www.acadlore.com/article/JISC/2023_2_2/jisc020203 This study undertakes a comprehensive review of control techniques applicable to DC-DC power converters, categorized into Traditional Control (TC) methods and those based on Artificial Intelligence (AI). Succinct descriptions of prevalent strategies in both classifications are furnished, shedding light on their fundamental principles. Further, the current progress in the field is evaluated, anchoring the discussion in the provided categorization. In assessing the merits and potential drawbacks of each method, specific emphasis is laid on the target converter topology. Predominant topologies such as the elementary buck, boost, bidirectional buck-boost, and dual-active-bridge (DAB) are scrutinized. To furnish a thorough analysis and facilitate comparison of principal control methods, simulations of four fundamental off-the-shelf algorithms are undertaken, employing a 1 MHz switching frequency. 06-28-2023 <![CDATA[ This study undertakes a comprehensive review of control techniques applicable to DC-DC power converters, categorized into Traditional Control (TC) methods and those based on Artificial Intelligence (AI). Succinct descriptions of prevalent strategies in both classifications are furnished, shedding light on their fundamental principles. Further, the current progress in the field is evaluated, anchoring the discussion in the provided categorization. In assessing the merits and potential drawbacks of each method, specific emphasis is laid on the target converter topology. Predominant topologies such as the elementary buck, boost, bidirectional buck-boost, and dual-active-bridge (DAB) are scrutinized. To furnish a thorough analysis and facilitate comparison of principal control methods, simulations of four fundamental off-the-shelf algorithms are undertaken, employing a 1 MHz switching frequency. ]]> Comparative Examination of Control Strategies in DC-DC Power Converters: A Traditional and Artificial Intelligence Perspective erik martínez-vera pedro bañuelos-sanchez gibran etcheverry doi: 10.56578/jisc020203 Journal of Intelligent Systems and Control 06-28-2023 Journal of Intelligent Systems and Control 06-28-2023 2023 2 2 Article 82 10.56578/jisc020203 https://www.acadlore.com/article/JISC/2023_2_2/jisc020203 https://www.acadlore.com/article/JISC/2023_2_2/jisc020202 This study presents an evaluation of a mathematical model designed for altitude and attitude control in quadcopters, employing Sliding Mode Control (SMC) in conjunction with the Kalman Filter algorithm. The developed mathematical model focuses on controlling the quadcopter's height along the z-axis and its attitude, encompassing roll, pitch, and yaw. Simulation results demonstrate that the quadcopter achieves stable control within a time span of 2 to 4 seconds. The designed control system has been simulated, implemented on a mini-quadcopter, and tested for the occurrence of chattering events. The incorporation of the SMC-Kalman Filter control system effectively mitigates chattering, resulting in enhanced stability for the quadcopter. This work show cases the potential of the proposed mathematical model in achieving precise and stable control in quadcopters, thus expanding the applicability of such systems in various applications. 06-05-2023 <![CDATA[ This study presents an evaluation of a mathematical model designed for altitude and attitude control in quadcopters, employing Sliding Mode Control (SMC) in conjunction with the Kalman Filter algorithm. The developed mathematical model focuses on controlling the quadcopter's height along the z-axis and its attitude, encompassing roll, pitch, and yaw. Simulation results demonstrate that the quadcopter achieves stable control within a time span of 2 to 4 seconds. The designed control system has been simulated, implemented on a mini-quadcopter, and tested for the occurrence of chattering events. The incorporation of the SMC-Kalman Filter control system effectively mitigates chattering, resulting in enhanced stability for the quadcopter. This work show cases the potential of the proposed mathematical model in achieving precise and stable control in quadcopters, thus expanding the applicability of such systems in various applications. ]]> Performance Evaluation of a Sliding Mode Control-Kalman Filter-Based Mathematical Model for Altitude and Attitude Control in Quadcopters purwadi agus darwito nilla perdana agustina doi: 10.56578/jisc020202 Journal of Intelligent Systems and Control 06-05-2023 Journal of Intelligent Systems and Control 06-05-2023 2023 2 2 Article 70 10.56578/jisc020202 https://www.acadlore.com/article/JISC/2023_2_2/jisc020202 https://www.acadlore.com/article/JISC/2023_2_2/jisc020201 In order to further improve the vibration energy harvesting efficiency of piezoelectric energy harvester under low frequency environmental excitation, this paper, based on the traditional magnetic tri-stable piezoelectric energy collector model, proposes a tri-stable piezoelectric energy harvester (TPEH+DEM) model with two elastic amplifiers which are installed between the U-shaped frame and the base and between the fixed end of the piezoelectric cantilever beam and the U-shaped frame respectively. Based on Hamilton principle, the motion equation of electromechanical coupling of TPEH+DEM system is established, and the analytical solutions of displacement, output voltage and power of the system are obtained by harmonic balance method. The effects of the mass of elastic amplifier, spring stiffness, magnet spacing and load resistance on the dynamic characteristics of energy harvesting of TPEH+DEM system are analyzed. The result shows that there are two peaks in the response output power of TPEH+DEM system in the operating frequency range. By adjusting the mass and stiffness of the elastic amplifier reasonably, the system can move into the inter-well motion under low external excitation intensity, and produce high output power. Compared with the traditional model which only has an elastic amplifier on the base of piezoelectric energy harvester, TPEH+DEM model has better energy harvesting performance under low frequency and low intensity external excitation. 04-02-2023 <![CDATA[ <p>In order to further improve the vibration energy harvesting efficiency of piezoelectric energy harvester under low frequency environmental excitation, this paper, based on the traditional magnetic tri-stable piezoelectric energy collector model, proposes a tri-stable piezoelectric energy harvester (TPEH+DEM) model with two elastic amplifiers which are installed between the U-shaped frame and the base and between the fixed end of the piezoelectric cantilever beam and the U-shaped frame respectively. Based on Hamilton principle, the motion equation of electromechanical coupling of TPEH+DEM system is established, and the analytical solutions of displacement, output voltage and power of the system are obtained by harmonic balance method. The effects of the mass of elastic amplifier, spring stiffness, magnet spacing and load resistance on the dynamic characteristics of energy harvesting of TPEH+DEM system are analyzed. The result shows that there are two peaks in the response output power of TPEH+DEM system in the operating frequency range. By adjusting the mass and stiffness of the elastic amplifier reasonably, the system can move into the inter-well motion under low external excitation intensity, and produce high output power. Compared with the traditional model which only has an elastic amplifier on the base of piezoelectric energy harvester, TPEH+DEM model has better energy harvesting performance under low frequency and low intensity external excitation.</p> ]]> Dynamic Characteristic Analysis of Tri-Stable Piezoelectric Energy Harvester with Double Elastic Amplifiers dawei man yingying bai qingnan hu huaiming xu gaozheng xu liping tang doi: 10.56578/jisc020201 Journal of Intelligent Systems and Control 04-02-2023 Journal of Intelligent Systems and Control 04-02-2023 2023 2 2 Article 54 10.56578/jisc020201 https://www.acadlore.com/article/JISC/2023_2_2/jisc020201 https://www.acadlore.com/article/JISC/2023_2_1/jisc020105 Direct current (DC) micromotors play a key role in micro robotic systems. The DC micromotor has a large market demand but there is a lack of theoretical research for it. The DC micromotor is still usable in many applications, despite the main problem that arises at the level of the connection between the brushes, or "carbons" and the rotary commutator. Mainly because their power circuit is simple to build. The main objective of this work is the evaluation by simulation under Simscape of the performance of Faulhaber permanent magnet DC micromotor and the study of its characteristics. Simulation results on MATLAB/Simscape software showed that a Simscape test bench is ultra-efficient for the study of electric drives. Students of engineering schools are thus prepared for the latest developments and real industrial requirements. 03-30-2023 <![CDATA[ Direct current (DC) micromotors play a key role in micro robotic systems. The DC micromotor has a large market demand but there is a lack of theoretical research for it. The DC micromotor is still usable in many applications, despite the main problem that arises at the level of the connection between the brushes, or "carbons" and the rotary commutator. Mainly because their power circuit is simple to build. The main objective of this work is the evaluation by simulation under Simscape of the performance of Faulhaber permanent magnet DC micromotor and the study of its characteristics. Simulation results on MATLAB/Simscape software showed that a Simscape test bench is ultra-efficient for the study of electric drives. Students of engineering schools are thus prepared for the latest developments and real industrial requirements. ]]> Characterization of the Direct Current Micromotor by Simscape ghlam karima oukli mimouna doi: 10.56578/jisc020105 Journal of Intelligent Systems and Control 03-30-2023 Journal of Intelligent Systems and Control 03-30-2023 2023 2 1 Article 47 10.56578/jisc020105 https://www.acadlore.com/article/JISC/2023_2_1/jisc020105 https://www.acadlore.com/article/JISC/2023_2_1/jisc020104 Objective of this study is to develop a novel, effective, and robust Sliding Mode Control (SMC) method for quadcopters (also called quadrotors) based on Adaptive Neuro-Fuzzy Inference System (ANFIS) for the purposes of enhancing trajectory tracking performance and realizing safe and reliable flight. In the paper, the ANFIS was combined with SMC technology to propose a scheme of adaptive robust controller, which is composed of three sub-controllers, x position controller, y position controller, and z position (altitude) controller. The proposed method can realize position tracking control of quadcopters in the presence of external disturbances. With the help of ANFIS, an adjustable gain rather than a fixed gain was established for the SMC controller, the optimal output could be attained based on a set of rules, and the position control gain was updated by ANFIS, enabling the SMC to adapt to environmental changes. Through modelling, simulation and comparison, experimental data verified that the proposed ANFIS-SMC controller outperformed conventional SMC controller in terms of convergence speed, robustness, accuracy, and stability with a maximum mean error of 0.125 meters in trajectory tracking. Research findings of this paper could contribute to the development of robust and responsive control strategies for Unmanned aerial vehicles (UAVs) trajectory tracking by providing valuable insights into the design of more effective and efficient control systems for UAVs, particularly in the context of dynamic environmental conditions. 03-30-2023 <![CDATA[ <p>Objective of this study is to develop a novel, effective, and robust Sliding Mode Control (SMC) method for quadcopters (also called quadrotors) based on Adaptive Neuro-Fuzzy Inference System (ANFIS) for the purposes of enhancing trajectory tracking performance and realizing safe and reliable flight. In the paper, the ANFIS was combined with SMC technology to propose a scheme of adaptive robust controller, which is composed of three sub-controllers, x position controller, y position controller, and z position (altitude) controller. The proposed method can realize position tracking control of quadcopters in the presence of external disturbances. With the help of ANFIS, an adjustable gain rather than a fixed gain was established for the SMC controller, the optimal output could be attained based on a set of rules, and the position control gain was updated by ANFIS, enabling the SMC to adapt to environmental changes. Through modelling, simulation and comparison, experimental data verified that the proposed ANFIS-SMC controller outperformed conventional SMC controller in terms of convergence speed, robustness, accuracy, and stability with a maximum mean error of 0.125 meters in trajectory tracking. Research findings of this paper could contribute to the development of robust and responsive control strategies for Unmanned aerial vehicles (UAVs) trajectory tracking by providing valuable insights into the design of more effective and efficient control systems for UAVs, particularly in the context of dynamic environmental conditions.</p> ]]> Adaptive Neuro-Fuzzy Inference System Based on Sliding Mode Control for Quadcopter Trajectory Tracking with the Presence of External Disturbance purwadi agus darwito nor indayu doi: 10.56578/jisc020104 Journal of Intelligent Systems and Control 03-30-2023 Journal of Intelligent Systems and Control 03-30-2023 2023 2 1 Article 33 10.56578/jisc020104 https://www.acadlore.com/article/JISC/2023_2_1/jisc020104 https://www.acadlore.com/article/JISC/2023_2_1/jisc020103 With the help of vector equations and MATLAB software, this paper studied the kinematics and kinetostatics of toggle-type transmission mechanism (hereinafter referred to as “toggle mechanism” for short) and attained the analytical expressions of displacement, speed, and acceleration of slider punch, and the force and moment balance equations of each component in the toggle mechanism with their inertia force taken into consideration. Then, the toggle mechanism was compared with conventional crank-link mechanism and their kinematic characteristics were comparatively analyzed. The proposed kinematics analysis method of toggle mechanism could figure out the kinematic characteristics of the target mechanism and reveal its operating advantages on the basis that its functional requirements are met, in this way, the research purpose of optimizing the design of the mechanism could be realized, and the attained conclusions could provide useful evidence for the design of other types of transmission mechanisms. 03-30-2023 <![CDATA[ With the help of vector equations and MATLAB software, this paper studied the kinematics and kinetostatics of toggle-type transmission mechanism (hereinafter referred to as “toggle mechanism” for short) and attained the analytical expressions of displacement, speed, and acceleration of slider punch, and the force and moment balance equations of each component in the toggle mechanism with their inertia force taken into consideration. Then, the toggle mechanism was compared with conventional crank-link mechanism and their kinematic characteristics were comparatively analyzed. The proposed kinematics analysis method of toggle mechanism could figure out the kinematic characteristics of the target mechanism and reveal its operating advantages on the basis that its functional requirements are met, in this way, the research purpose of optimizing the design of the mechanism could be realized, and the attained conclusions could provide useful evidence for the design of other types of transmission mechanisms. ]]> A Vector Equation Method for Analyzing Kinematics and Kinetostatics of Toggle-Type Transmission Mechanism bing yang doi: 10.56578/jisc020103 Journal of Intelligent Systems and Control 03-30-2023 Journal of Intelligent Systems and Control 03-30-2023 2023 2 1 Article 23 10.56578/jisc020103 https://www.acadlore.com/article/JISC/2023_2_1/jisc020103 https://www.acadlore.com/article/JISC/2023_2_1/jisc020102 Due to simple structure, easy maintenance and low cost, induction motors (IMs) are widely applied in various industries, accounting for 60-80% alternating current (AC) motors used in industry. However, the efficiency of IMs is very low, and even small improvement can result in significant energy saving. For instance, 1% efficiency increase saves billions of kilowatt hours. Therefore, this paper aimed to improve the efficiency of IMs, thus reducing energy consumption and greenhouse gas emissions. For an IM with 7.5kW rated power and IE3 energy efficiency, the efficiency is improved by making various changes. Sequential quadratic algorithm and fmincon function are proposed to change the rotor slot and teeth structures, realizing nearly 91% motor efficiency, which is a significant improvement over the original efficiency. It is worth noting that improving the efficiency of IMs saves a lot of energy, especially in cases where IMs account for a large proportion of AC motors. 03-28-2023 <![CDATA[ <p>Due to simple structure, easy maintenance and low cost, induction motors (IMs) are widely applied in various industries, accounting for 60-80% alternating current (AC) motors used in industry. However, the efficiency of IMs is very low, and even small improvement can result in significant energy saving. For instance, 1% efficiency increase saves billions of kilowatt hours. Therefore, this paper aimed to improve the efficiency of IMs, thus reducing energy consumption and greenhouse gas emissions. For an IM with 7.5kW rated power and IE3 energy efficiency, the efficiency is improved by making various changes. Sequential quadratic algorithm and fmincon function are proposed to change the rotor slot and teeth structures, realizing nearly 91% motor efficiency, which is a significant improvement over the original efficiency. It is worth noting that improving the efficiency of IMs saves a lot of energy, especially in cases where IMs account for a large proportion of AC motors.</p> ]]> Efficiency Improvement of Induction Motors Based on Rotor Slot and Tooth Structures hung bui duc chi-phi do manh doan cong vuong dang quoc doi: 10.56578/jisc020102 Journal of Intelligent Systems and Control 03-28-2023 Journal of Intelligent Systems and Control 03-28-2023 2023 2 1 Article 13 10.56578/jisc020102 https://www.acadlore.com/article/JISC/2023_2_1/jisc020102 https://www.acadlore.com/article/JISC/2023_2_1/jisc020101 Nowadays more and more devices and appliances are operated with electricity, thus the electrical crisis is increasing exponentially day by day. In order to avoid the occurrence of electricity crisis, various power generation resources are used at the utility side to enhance the power generation to meet the consumers’ demand for electricity. Hence, a suitable control scheme has to be implemented at the microgrid to reduce the electrical fluctuation, power loss and manage the power quality. The Adaptive Proportional Integral Voltage Controller (APIVC) and hysteresis current controller (HCC) are integrated to enhance the quality of power generated. The electrical fluctuation is reduced by the proposed efficient hybrid parallel source controller model for DC Microgrid. The proposed model exerts decentralized control, which is an advanced droop control where communication is not required. The outer voltage control loop and inner current control loop provide faster control to maintain the grid voltage constant. The grid voltage is set as the reference value and the actual value is sensed to generate error value, which sets the reference value of current. The error signal is processed to provide switching signals for the converters. The performance analysis and simulation results show that the proposed mechanism performed better than the conventional methods such as Hysteresis Band Current Controller (HBCC) with Pulse Width Modulation (PWM) and Proportional Integral Voltage Controller (PIVC) with Hysteresis Current Controller (HCC), in terms of the electrical fluctuation, power loss and manage the power quality in the microgrid. 03-28-2023 <![CDATA[ <p>Nowadays more and more devices and appliances are operated with electricity, thus the electrical crisis is increasing exponentially day by day. In order to avoid the occurrence of electricity crisis, various power generation resources are used at the utility side to enhance the power generation to meet the consumers’ demand for electricity. Hence, a suitable control scheme has to be implemented at the microgrid to reduce the electrical fluctuation, power loss and manage the power quality. The Adaptive Proportional Integral Voltage Controller (APIVC) and hysteresis current controller (HCC) are integrated to enhance the quality of power generated. The electrical fluctuation is reduced by the proposed efficient hybrid parallel source controller model for DC Microgrid. The proposed model exerts decentralized control, which is an advanced droop control where communication is not required. The outer voltage control loop and inner current control loop provide faster control to maintain the grid voltage constant. The grid voltage is set as the reference value and the actual value is sensed to generate error value, which sets the reference value of current. The error signal is processed to provide switching signals for the converters. The performance analysis and simulation results show that the proposed mechanism performed better than the conventional methods such as Hysteresis Band Current Controller (HBCC) with Pulse Width Modulation (PWM) and Proportional Integral Voltage Controller (PIVC) with Hysteresis Current Controller (HCC), in terms of the electrical fluctuation, power loss and manage the power quality in the microgrid.</p> ]]> Design and Implementation of Hybrid Controller for Dynamic Power Management in a DC Microgrid sharmila nagaraju nataraj kanathur ramaswamy rekha kanathur ramaswamy doi: 10.56578/jisc020101 Journal of Intelligent Systems and Control 03-28-2023 Journal of Intelligent Systems and Control 03-28-2023 2023 2 1 Article 1 10.56578/jisc020101 https://www.acadlore.com/article/JISC/2023_2_1/jisc020101 https://www.acadlore.com/article/JISC/2022_1_1/jisc010108 This paper mainly explores the system identification and control of an automatic car pedal pressing system. Specifically, the system identification was achieved using an artificial neural network, with the help of MATLAB’s System Identification Toolbox. The proportional-integral-derivative (PID) controller and fuzzy logic controller were designed, and normalized with membership functions. These functions were scaled with a gain as a scaling factor. The controller gains were tuned by a metaheuristic algorithm named particle swarm optimization (PSO). On this basis, the two controllers were compared with a number of performance indices, including integral squared error (ISE), integral absolute error (IAE), integral time absolute error (ITAE), and mean squared error (MSE). The car pedal pressing performance was measured at different speed levels for each controller. 10-29-2022 <![CDATA[ <p>This paper mainly explores the system identification and control of an automatic car pedal pressing system. Specifically, the system identification was achieved using an artificial neural network, with the help of MATLAB’s System Identification Toolbox. The proportional-integral-derivative (PID) controller and fuzzy logic controller were designed, and normalized with membership functions. These functions were scaled with a gain as a scaling factor. The controller gains were tuned by a metaheuristic algorithm named particle swarm optimization (PSO). On this basis, the two controllers were compared with a number of performance indices, including integral squared error (ISE), integral absolute error (IAE), integral time absolute error (ITAE), and mean squared error (MSE). The car pedal pressing performance was measured at different speed levels for each controller.</p> ]]> System Identification and Control of Automatic Car Pedal Pressing System lai chong jin azrul azim abdullah hashim salmiah ahmad nor maniha abdul ghani doi: 10.56578/jisc010108 Journal of Intelligent Systems and Control 10-29-2022 Journal of Intelligent Systems and Control 10-29-2022 2022 1 1 Article 79 10.56578/jisc010108 https://www.acadlore.com/article/JISC/2022_1_1/jisc010108 https://www.acadlore.com/article/JISC/2022_1_1/jisc010107 This study designs a reconfigurable multi-cloud storage server architecture for dynamic and secure data sharing has been designed, improves the security of unstructured data using cryptographic index-based data slicing (CIBDS), and reduces the malicious insider through data encryption using a third data encryption algorithm (3DEA). Focusing on multi-cloud storage server (MCSS) and data life cycle which includes three stages (i.e., data input, transition and utilization), the authors determined the efficiency of reconfigurable data file slicing, standard format, privacy and trustworthiness of the customers, in contrast to existing methods. Every part of a data file was encrypted using 3DEA, and Rivest Shamir Adleman (RSA) was employed to produce the private key to secure the unstructured data. The results show that the proposed framework effectively searches the data files in MCSS based on tags, such as input file names and private keys. The performance of the framework was measured by the security level, uploading/downloading latency time between our method and conventional methods, under different data sizes in (MB). Overall, our method reduces the malicious insider to 0.23% using 3DEA and RSA, during data encryption in the existing USDS-MC, shortens the uploading/downloading latency time (s) by 10% and 12%, compared to USDS-MC, and enhances the unstructured data security by 12% in comparison with that method. In this way, the authors managed to improve the self-protection of reconfigurable and secure unstructured data files in huge cloud infrastructure. This research optimizes the data security and privacy of encryption, decryption and cryptography technologies, and helps with the online process and its security maintenance during cloud storage. 10-29-2022 <![CDATA[ <p>This study designs a reconfigurable multi-cloud storage server architecture for dynamic and secure data sharing has been designed, improves the security of unstructured data using cryptographic index-based data slicing (CIBDS), and reduces the malicious insider through data encryption using a third data encryption algorithm (3DEA). Focusing on multi-cloud storage server (MCSS) and data life cycle which includes three stages (i.e., data input, transition and utilization), the authors determined the efficiency of reconfigurable data file slicing, standard format, privacy and trustworthiness of the customers, in contrast to existing methods. Every part of a data file was encrypted using 3DEA, and Rivest Shamir Adleman (RSA) was employed to produce the private key to secure the unstructured data. The results show that the proposed framework effectively searches the data files in MCSS based on tags, such as input file names and private keys. The performance of the framework was measured by the security level, uploading/downloading latency time between our method and conventional methods, under different data sizes in (MB). Overall, our method reduces the malicious insider to 0.23% using 3DEA and RSA, during data encryption in the existing USDS-MC, shortens the uploading/downloading latency time (s) by 10% and 12%, compared to USDS-MC, and enhances the unstructured data security by 12% in comparison with that method. In this way, the authors managed to improve the self-protection of reconfigurable and secure unstructured data files in huge cloud infrastructure. This research optimizes the data security and privacy of encryption, decryption and cryptography technologies, and helps with the online process and its security maintenance during cloud storage.</p> ]]> An Efficient Reconfigurable Cryptographic Model for Dynamic and Secure Unstructured Data Sharing in Multi-Cloud Storage Server parashiva murthy basavanapura muddumadappa sumithra devi kengeri anjanappa mallikarjunaswamy srikantaswamy doi: 10.56578/jisc010107 Journal of Intelligent Systems and Control 10-29-2022 Journal of Intelligent Systems and Control 10-29-2022 2022 1 1 Article 68 10.56578/jisc010107 https://www.acadlore.com/article/JISC/2022_1_1/jisc010107 https://www.acadlore.com/article/JISC/2022_1_1/jisc010106 The rising power demand has forced power systems all over the world to operate very close to their stability limits. When power systems are overloaded, faulty, or in lack of reactive power, voltage collapses would ensue. The capacity of a power system to keep the voltage of every bus constant under disturbances is called voltage stability. This dynamic phenomenon hinges on the load features. It is commonly known that flexible AC transmission systems (FACTS) can improve voltage stability. This paper puts forward a load flow model with the unified power flow controller (UPFC), and relies on the model to investigate the voltage stability of a power system through continuation power flow (CPF) method. The validity of the model was verified through a simulation, using the power system analysis toolbox (PSAT) in MATLAB/Simulink environment. 10-29-2022 <![CDATA[ <p>The rising power demand has forced power systems all over the world to operate very close to their stability limits. When power systems are overloaded, faulty, or in lack of reactive power, voltage collapses would ensue. The capacity of a power system to keep the voltage of every bus constant under disturbances is called voltage stability. This dynamic phenomenon hinges on the load features. It is commonly known that flexible AC transmission systems (FACTS) can improve voltage stability. This paper puts forward a load flow model with the unified power flow controller (UPFC), and relies on the model to investigate the voltage stability of a power system through continuation power flow (CPF) method. The validity of the model was verified through a simulation, using the power system analysis toolbox (PSAT) in MATLAB/Simulink environment.</p> ]]> Continuation Power Flow Analysis of Power System Voltage Stability with Unified Power Flow Controller youcef islam djilani kobibi mohamed abdeldjalil djehaf mohamed khatir mohamed ouadafraksou doi: 10.56578/jisc010106 Journal of Intelligent Systems and Control 10-29-2022 Journal of Intelligent Systems and Control 10-29-2022 2022 1 1 Article 60 10.56578/jisc010106 https://www.acadlore.com/article/JISC/2022_1_1/jisc010106 https://www.acadlore.com/article/JISC/2022_1_1/jisc010105 The overhead crane is a typical underactuated system with complicated dynamics and strong couplings. It is widely employed to transport heavy cargoes in many industrial fields. Due to the complexity of working environments, however, cranes often encounter various unfavorable factors, which may degrade the transportation efficiency. To enhance control performance and anti-disturbance ability, this paper proposes an active disturbance rejection control approach based on differential flatness for double pendulum cranes with variable rope lengths. The proposed approach can position the trolley accurately, regulate rope length, and suppress the swing angles of the payload and the hook simultaneously. During the controller design, flat outputs were constructed based on differential flatness technique to deal with system couplings, and the results prove that double pendulum crane system is differentially flat. After that, model uncertainties and external disturbances were estimated by the designed extended state observer. On this basis, a controller was developed based on the feedback control technique. Finally, a series of simulations were carried out to show that the control scheme is effective and robust. 10-29-2022 <![CDATA[ <p>The overhead crane is a typical underactuated system with complicated dynamics and strong couplings. It is widely employed to transport heavy cargoes in many industrial fields. Due to the complexity of working environments, however, cranes often encounter various unfavorable factors, which may degrade the transportation efficiency. To enhance control performance and anti-disturbance ability, this paper proposes an active disturbance rejection control approach based on differential flatness for double pendulum cranes with variable rope lengths. The proposed approach can position the trolley accurately, regulate rope length, and suppress the swing angles of the payload and the hook simultaneously. During the controller design, flat outputs were constructed based on differential flatness technique to deal with system couplings, and the results prove that double pendulum crane system is differentially flat. After that, model uncertainties and external disturbances were estimated by the designed extended state observer. On this basis, a controller was developed based on the feedback control technique. Finally, a series of simulations were carried out to show that the control scheme is effective and robust.</p> ]]> Active Disturbance Rejection Control Approach for Double Pendulum Cranes with Variable Rope Lengths xinya yao he chen zhenyue fan doi: 10.56578/jisc010105 Journal of Intelligent Systems and Control 10-29-2022 Journal of Intelligent Systems and Control 10-29-2022 2022 1 1 Article 46 10.56578/jisc010105 https://www.acadlore.com/article/JISC/2022_1_1/jisc010105 https://www.acadlore.com/article/JISC/2022_1_1/jisc010104 For a class of system with nonlinear hysteresis, this paper presents an adaptive hybrid controller based on the hybrid backstepping-sliding mode, and describes the controller analytically by the LuGre model. Both backstepping and the sliding mode techniques are based on the Lyapunov theory. Drawing on this common point, the authors developed a new controller combining the two control techniques with a recursive design. The design aims to achieve two effects: assuring the stability of the closed loop system, and improving the continuous performance of the tracking position trajectory. The performance of the proposed hybrid controller was verified by implementing the identified Piezo model. The results show that our controller can track the system output desirably with the reference trajectory. 10-29-2022 <![CDATA[ <p>For a class of system with nonlinear hysteresis, this paper presents an adaptive hybrid controller based on the hybrid backstepping-sliding mode, and describes the controller analytically by the LuGre model. Both backstepping and the sliding mode techniques are based on the Lyapunov theory. Drawing on this common point, the authors developed a new controller combining the two control techniques with a recursive design. The design aims to achieve two effects: assuring the stability of the closed loop system, and improving the continuous performance of the tracking position trajectory. The performance of the proposed hybrid controller was verified by implementing the identified Piezo model. The results show that our controller can track the system output desirably with the reference trajectory.</p> ]]> Hybrid Approach Control of Micro-Positioning Stage with a Piezoelectric Actuator ounissi amor azeddine kaddouri rachid abdessemed doi: 10.56578/jisc010104 Journal of Intelligent Systems and Control 10-29-2022 Journal of Intelligent Systems and Control 10-29-2022 2022 1 1 Article 35 10.56578/jisc010104 https://www.acadlore.com/article/JISC/2022_1_1/jisc010104 https://www.acadlore.com/article/JISC/2022_1_1/jisc010103 Hydrogen production by wind and solar hybrid power generation is an important means to solve the strong randomness and high volatility of wind and solar power generation. In this paper, the permanent magnet direct-drive wind turbine, photovoltaic power generation unit, battery pack, and electrolyzer are assembled in the AC bus, and the mathematical model of the wind-solar hydrogen storage coupled power generation system and the simulation model in PSCAD/EMTDC are established. An energy coordination control strategy is designed. After simulation, the proposed control strategy can effectively reduce the rate of curtailment of wind and solar power, and stabilize the fluctuation of wind and solar power generation. It verifies that the established model is correct and the control strategy is effective and feasible. 10-29-2022 <![CDATA[ <p>Hydrogen production by wind and solar hybrid power generation is an important means to solve the strong randomness and high volatility of wind and solar power generation. In this paper, the permanent magnet direct-drive wind turbine, photovoltaic power generation unit, battery pack, and electrolyzer are assembled in the AC bus, and the mathematical model of the wind-solar hydrogen storage coupled power generation system and the simulation model in PSCAD/EMTDC are established. An energy coordination control strategy is designed. After simulation, the proposed control strategy can effectively reduce the rate of curtailment of wind and solar power, and stabilize the fluctuation of wind and solar power generation. It verifies that the established model is correct and the control strategy is effective and feasible.</p> ]]> Modeling and Control Strategy of Wind-Solar Hydrogen Storage Coupled Power Generation System tianze yuan hua li dong jia doi: 10.56578/jisc010103 Journal of Intelligent Systems and Control 10-29-2022 Journal of Intelligent Systems and Control 10-29-2022 2022 1 1 Article 18 10.56578/jisc010103 https://www.acadlore.com/article/JISC/2022_1_1/jisc010103 https://www.acadlore.com/article/JISC/2022_1_1/jisc010102 Creating a fair replenishment strategy is one of the most significant instruments in the inventory management for automotive spare parts. It is also crucial to controlling the enterprise's inventory level. This study considers the significance of retailers' demand forecasting at the conclusion of the sales period to build a lateral transfer inventory optimization scheme with high scientific rigor, aiming to ensure the correctness and logic of the replenishment strategy. To provide a more scientific direction for the inventory management of an automotive spare parts company, this research constructs an upgraded particle swarm optimization (PSO)-backpropagation (BP) neural network prediction model, and a lateral transfer inventory optimization method based on demand forecasting. Finally, 26 retailers of Company B in Central China's Hunan Province were taken as examples to confirm the model's efficacy. The outcomes demonstrate an improvement in the lateral transfer's applicability in Company B. 10-29-2022 <![CDATA[ <p>Creating a fair replenishment strategy is one of the most significant instruments in the inventory management for automotive spare parts. It is also crucial to controlling the enterprise's inventory level. This study considers the significance of retailers' demand forecasting at the conclusion of the sales period to build a lateral transfer inventory optimization scheme with high scientific rigor, aiming to ensure the correctness and logic of the replenishment strategy. To provide a more scientific direction for the inventory management of an automotive spare parts company, this research constructs an upgraded particle swarm optimization (PSO)-backpropagation (BP) neural network prediction model, and a lateral transfer inventory optimization method based on demand forecasting. Finally, 26 retailers of Company B in Central China's Hunan Province were taken as examples to confirm the model's efficacy. The outcomes demonstrate an improvement in the lateral transfer's applicability in Company B.</p> ]]> Optimization of Lateral Transfer Inventory of Auto Spare Parts Based on Neural Network Forecasting xinhao shao daofang chang meijia li doi: 10.56578/jisc010102 Journal of Intelligent Systems and Control 10-29-2022 Journal of Intelligent Systems and Control 10-29-2022 2022 1 1 Article 2 10.56578/jisc010102 https://www.acadlore.com/article/JISC/2022_1_1/jisc010102 https://www.acadlore.com/article/JISC/2022_1_1/jisc010101 10-29-2022 <![CDATA[ ]]> Editorial to the Inaugural Issue he chen doi: 10.56578/jisc010101 Journal of Intelligent Systems and Control 10-29-2022 Journal of Intelligent Systems and Control 10-29-2022 2022 1 1 Article 1 10.56578/jisc010101 https://www.acadlore.com/article/JISC/2022_1_1/jisc010101