Owing to its superior efficiency, power density, and reduced maintenance requirements, the brushless DC motor (BLDC) has found extensive applications in household devices, electric vehicles, and industrial automation systems. However, the nonlinear commutation characteristic and the torque pulsation caused by the trapezoidal wave of the back electromotive force make the traditional PID control have the defects of large overshot and low speed jitter in the wide speed range. To enhance dynamic responsiveness and disturbance rejection capabilities, this study introduces a self-tuning fuzzy PID control framework that adaptively modifies the speed-loop PID parameters in real-time.Firstly, the mathematical model of BLDC motor is established, including voltage equation, back electromotive force characteristic and torque-motion equation, and a fuzzy controller is designed based on double closed-loop control architecture (outer loop fuzzy PID adjusting speed, inner loop PI controlling current). The controller takes speed error and error change rate as input, outputs PID parameter increment, and realizes parameter dynamic adjustment by fuzzy rule base and gravity center method. The proposed methodology establishes a foundational framework for high-precision BLDC motor control, demonstrating significant applicability in industrial motion control scenarios.
Wang et al. (Tue,) studied this question.