Particle swarm optimised fuzzy PID control method for hybrid magnetic bearings

To enhance the control effectiveness of hybrid magnetic bearings (HMBs), this paper proposes a PSO-based fuzzy PID control algorithm. The algorithm optimizes the fuzzy controller's output parameters using the Particle Swarm Optimization technique, effectively addressing the limitations caused by fixed parameters and improving control accuracy. The effectiveness of the PSO algorithm optimization is verified through simulations of a hybrid magnetic bearing system built in Simulink. Compared to the fuzzy PID control algorithm, this method demonstrates a faster response and smaller overshoot, achieving better results in controlling the vibration displacement of rotors supported by hybrid magnetic bearings.