PID Control of Permanent Magnet Synchronous Motor Based on Improved Actor-Critic Framework

Aiming at the shortcomings of the traditional PID control method that the parameters cannot be adjusted flexible, an improved Actor-Critic reinforcement learning algorithm combined with incremental PID control is proposed to improve the control performance of permanent magnet synchronous motor (PMSM). The strategy function of Actor and value function of Critic are approximated by two back propagation (BP) neural networks respectively. The simulation results show that the proposed algorithm has better control performance and effect than the traditional PID control method.