Development of Adaptive Fuzzy PID Controller Integrated with Slide Mode Control for Brushless Direct Current Motors

The relationship between magnetic flux and speed in a BLDC motor is complex and will show different trends under different control methods. Add the gap, other research has been done but still this issue is there. This study focuses on analyzing the relationship between magnetic flux and speed in a BLDC motor, using a proportional-integral-derivative (PID) control system with the inner loop acting as the current outer loop, investigating the performance of the fuzzy controller, and using three control methods, the traditional PID control, fuzzy PID control and adaptive PID control. The simulation uses the BLDC to simulate at 30%, 50%, and 100% of the rated speed, and verifies that the system can adjust the PID parameters in different situations and different control modes. At the same time, since harmonic distortion will be generated in the circuit, an adaptive filter is introduced, which acts as an integral filter at the operating frequency while suppressing other frequency components to balance control performance and stability. The experimental results show that the adaptive fuzzy control can reach a desired output state faster in only 0.665s, while the fuzzy PID control needs 0.693s, and the traditional fuzzy PID needs 0.696s. It can be proved that the traditional PID parameters are difficult to adjust, and it is difficult to achieve the best effect of magnetic flux and speed. On top of that, the optimized adaptive fuzzy PID controller has faster response speed, smaller overshoot, higher control precision, and can control the motor speed output more effectively.