Permanent Magnet Motor Control System Based on Fuzzy PID Control

Abstract

Although the traditional permanent magnet synchronous motor control system is simple and convenient, the control of speed and accuracy is often affected by external interference, which impacts the dynamic and static performance requirements. Therefore, this study attempts to introduce fuzzy rules to improve the proportional integral differential control method, and further integrate intelligent optimization algorithms into the fuzzy proportional integral differential control method to construct an efficient and feasible permanent magnet synchronous motor control method. The simulation experiment demonstrates that under fuzzy proportional integral differential control, there is no overshoot in the waveform when facing changes in load, and the tuning time increases from 0.01 seconds to 0.12 seconds. The steady-state error of speed control is small, and there is no obvious oscillation in the waveform. Fuzzy control enhances the control system. After the optimization of the artificial bee colony algorithm, the control system has a faster speed response, with the overshoot diminished from 11.2% to 3.1%, and the adjustment time reduced from 0.27 seconds to 0.19 seconds, enhancing its adaptability. Under load regulation, the optimized control system speed response curve responds in a timely manner without obvious overshooting and oscillating changes. Optimizing variable universe fuzzy proportional integral differential control enables the control system for having better static and dynamic performance, and enhances the adaptability and follow-up of the control system. The current curve starts to stabilize at 0.04s, overcoming the control system oscillations early. The speed response curve and the motor torque curve are improved by the optimized variable domain theory, and the amount of overshoot is significantly reduced. The research and design of a permanent magnet motor control system has practical significance for improving the application performance and adaptability of permanent magnet motors.