PID controller enhanced with artificial bee colony algorithm for active magnetic bearing

Abstract

To reduce the effect of non-linearity in air gap control in active magnetic bearings (AMB). The PID controller for the AMB is proposed in this study, which is optimized with a reformative artificial bee colony (RABC) algorithm. The RABC algorithm balances the exploitation and exploration capabilities of the ABC algorithm by introducing globally optimal solutions and improved food source probabilities. Simulation with six benchmark functions validates the proposed algorithm, and the results reveal that the RABC algorithm has higher search accuracy and faster search speed than previous ABC algorithm versions. The experimental results show that RABC-PID outperforms the other four approaches and has greater robustness when compared to traditional PID, PSO-PID, DE-PID, and GA-PID. Meanwhile, the RABC-PID controller makes the AMB system more stable.