Comparative Study of PMSM Control Using Reinforcement Learning and PID Control

The use of reinforcement learning for process control does not require knowledge of its mathematical model. This paper focuses on the control of a permanent magnet synchronous motor (PMSM) based on the Field Oriented Control strategy (FOC). The objective is to compare the performances of the classical PID control with that using reinforcement learning (RL). The RL algorithm used is Double Delay Deterministic Policy Gradient (TD3). First, the general principle of vector control of a PMSM motor is described. Then, the control using reinforcement learning is analyzed and compared to PID control. The performances to be compared are accuracy, dynamic response and the ability to control torque and speed. Finally, the simulation models have been developed and tested in the MATLAB / SIMULINK. Simulated results are displayed to validate the effectiveness of the proposed strategies.