This paper aims at increasing the control effect of hybrid magnetic bearings(HMB). In this paper, a Fuzzy-PID control algorithm is used to control the HMB with complex and multivariate characteristics. And the Particle Swarm Optimization (PSO) algorithm is combined to optimize the scale factor parameters of the Fuzzy controller to solve the problem of fixed parameters of the Fuzzy controller, which leads to the limitation of control accuracy. A Simulink model of the HMB system considering the mass of the rotor is built, and the response of the rotor to float and the response under the action of external disturbance forces are simulated respectively. The results show that after optimisation by the PSO algorithm, the system responds quickly, with small overshoot and high stability, which achieves better control results in the process of rotor displacement control of the hybrid magnetic bearing support.

This paper aims at increasing the control effect. In this paper, a fuzzy PID control algorithm is used to control the hybrid magnetic bearings(HMBS) with complex and multivariate characteristics. And the particle swarm optimization (PSO) algorithm is combined to optimize the scale factors of the fuzzy controller to solve the problem of fixed parameters of the fuzzy controller, which leads to the limitation of control accuracy. The simulation of the HMB in Simulink, comparing PID and fuzzy PID control, shows that after the optimization of the PSO algorithm, the system response is quick and the overshoot is minimal, and better control results are achieved in the process of rotor displacement control of the HMB support.