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Aiming at the poor transient convergence and real-time performance of the horizontal vibration state variables of the high-speed elevator car system, and the low control accuracy and stability, this paper proposes an adaptive control strategy to ensure the transient response of the elevator car system. First, a prescribed preset transient performance function is introduced into the controller design to control the variation range of the state variables and ensure the steady transient performance of the elevator car; Second, representing the information of observation error/control error through algebraic operations, designing an adaptive law based on e-correction, estimating unknown parameters in the elevator car system, and achieving online parameter updates; Then, using neural networks to learn and compensate for unknown dynamics in the elevator car system, and solving the online estimation problem of neural network weights through adaptive laws, so that the tracking error and weight estimation error converge to a tight set near zero; Finally, using MATLAB/SIMULINK to compare and analyze the four control algorithms of passive control, PID control, adaptive control based on gradient descent method and transient response adaptive control proposed in this paper under two different rail excitations: Random excitation and pulse excitation. The simulation results show that the adaptive control strategy proposed in this paper effectively suppresses the horizontal vibration of the elevator car, makes the state variables have faster convergence speed and smaller convergence error, and ensures the stable and transient performance of the elevator car system.
Aiming at the poor transient convergence and real-time performance of the horizontal vibration state variables of the high-speed elevator car system, and the low control accuracy and stability, this paper proposes an adaptive control strategy to ensure the transient response of the elevator car system. First, a prescribed preset transient performance function is introduced into the controller design to control the variation range of the state variables and ensure the steady transient performance of the elevator car; Second, representing the information of observation error/control error through algebraic operations, designing an adaptive law based on e-correction, estimating unknown parameters in the elevator car system, and achieving online parameter updates; Then, using neural networks to learn and compensate for unknown dynamics in the elevator car system, and solving the online estimation problem of neural network weights through adaptive laws, so that the tracking error and weight estimation error converge to a tight set near zero; Finally, using MATLAB/SIMULINK to compare and analyze the four control algorithms of passive control, PID control, adaptive control based on gradient descent method and transient response adaptive control proposed in this paper under two different rail excitations: Random excitation and pulse excitation. The simulation results show that the adaptive control strategy proposed in this paper effectively suppresses the horizontal vibration of the elevator car, makes the state variables have faster convergence speed and smaller convergence error, and ensures the stable and transient performance of the elevator car system.
The paper partially covered Active Constrained Layer Damping (ACLD) cantilever beams’ dynamic modeling, active vibration control, and parameter optimization techniques as the main topic of this research. The dynamic model of the viscoelastic sandwich beam is created by merging the finite element approach with the Golla Hughes McTavish (GHM) model. The governing equation is constructed based on Hamilton’s principle. After the joint reduction of physical space and state space, the model is modified to comply with the demands of active control. The control parameters are optimized based on the Kalman filter and genetic algorithm. The effect of various ACLD coverage architectures and excitation signals on the system’s vibration is investigated. According to the research, the genetic algorithm’s optimization iteration can quickly find the best solution while achieving accurate model tracking, increasing the effectiveness and precision of active control. The Kalman filter can effectively suppress the impact of vibration and noise exposure to random excitation on the system.
The flexible arm easily vibrates due to its thin structural characteristics, which affect the operation accuracy, so reducing the vibration of the flexible arm is a significant issue. Smart materials are very widely used in the research topic of vibration suppression. Considering the hysteresis characteristic of the smart materials, based on previous simulation research, this paper proposes an experimental system design of nonlinear vibration control by using the interactive actuation from shape memory alloy (SMA) for a flexible arm. The experiment system was an interactive actuator–sensor–controller combination. The vibration suppression strategy was integrated with an operator-based vibration controller, a designed integral compensator and the designed n-times feedback loop. In detail, a nonlinear vibration controller based on operator theory was designed to guarantee the robust stability of the flexible arm. An integral compensator based on an estimation mechanism was designed to optimally reduce the displacement of the flexible arm. Obtaining the desired tracking performance of the flexible arm was a further step, by increasing the n-times feedback loop. From the three experimental cases, when the vibration controller was integrated with the designed integral compensator, the vibration displacement of the flexible arm was much reduced compared to that without the integral compensator. Increasing the number of n-times feedback loops improves the tracking performance. The desired vibration control performance can be satisfied when n tends to infinity. The conventional PD controller stabilizes the vibration displacement after the 7th vibration waveform, while the vibration displacement approaches zero after the 4th vibration waveform using the proposed vibration control method, which is proved to be faster and more effective in controlling the flexible arm’s vibration. The experimental cases verify the effectiveness of the proposed interactive actuation vibration control approach. It is observed from the experimental results that the vibration displacement of the flexible arm becomes almost zero within less time and with lower input power, compared with a traditional controller.
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