Research on speed and torque parameter adaptive control system of permanent magnet synchronous motor

Permanent magnet synchronous motor (PMSM) is a multivariable, nonlinear and strongly coupled system. It is difficult to achieve the ideal control effect by using the basic proportional integral (PI) control method in the process of speed change and load disturbance. In this paper, an adaptive PI parameter control strategy for speed and torque is proposed. First, the optimal control parameters are obtained by the iterative learning. Then, the Adaptive Neuro-Fuzzy Inference System(ANFIS) learns from iterative learning results to achieve the system membership function parameters and control rules adjustment. Finally, the simulation results show that the system is characterized by high efficiency, high speed, high accuracy, small static response error, less response time and small overshoot. It is suitable for each torque transition and different operating speeds, which is superior to the basic PI control and fuzzy PI control with high control precision, good dynamic performance and strong anti-interference ability.