Stepping quantum genetic algorithm-based LQR control strategy for lateral vibration of high-speed elevator
Li Li, Tian Qiu, Tichang Jia, Chen Chen
Abstract
Abstract To effectively restrain the lateral vibration caused by the guide rail excitation and improve the ride comfort of the car system, a state-weighted linear quadratic regulator (LQR) control strategy is proposed. Firstly, based on the active control model of the 4-DOF car system with actuators distributed diagonally along the center of the car frame, an LQR controller for lateral vibration of high-speed elevator car systems is designed. Furthermore, in view of the tedious and time-consuming of the empirical method to choose state-weighted matrix Q , stepping quantum genetic algorithm (SQGA) is proposed to improve the performance of the controller. Finally, the time-frequency characteristic curves of the lateral vibration acceleration and the vibration displacement of the car system are compared and analyzed by MATLAB to verify the effectiveness of the proposed controller.