Study on the LQR Control of High-speed Elevator Car Horizontal Vibration Based on the Jumping Inertia Weight Particle Swarm Optimization

Abstract

To reduce the horizontal vibration of a high-speed elevator car caused by the excitation of a guide rail more effectively, a differential magnetic suspension active guide shoe based on the principle of the differential magnetic suspension actuator is designed. Then the dynamic model of the active vibration damping system of the elevator car is established and an LQR controller is designed to reduce the horizontal vibration of the car. To search the weighting coefficient matrix of the LQR controller more efficiently, an algorithm named Jumping inertia Weight Particle Swarm Optimization (JWPSO) algorithm is proposed, and the frequently used fitness function verifies the optimization effect of the JWPSO algorithm. The weighting coefficient matrix of the LQR controller is optimized using the JWPSO algorithm. Finally, the impact of the JWPSO algorithm-optimized LQR controller is verified by MATLAB. The simulation result shows that the designed active vibration controller can effectively attenuate the horizontal vibration of the elevator car, and the control effect is significantly better than the LQR controller optimized by the GA algorithm and the H-inf controller optimized by LMI. This paper provided a new method for horizontal vibration reduction of the high-speed elevator car.