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.

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.

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.