Comparative Performance Analysis of PID and Fuzzy-PID Speed Controllers for Brushless DC Motor Drives

Abstract

Proportional-Integral-Derivative (PID) controllers are effectively and widely used in various industries due to their ease of use and versatility. The Brushless DC (BLDC) motor is a well-known motor that combines reliability and efficiency, but for optimal performance, speed control must be precise. Although useful and often treated as a ‘black box’, PID controllers require careful tuning to achieve optimal performance in applications. This study describes a comparative study of two PID controllers for BLDC motors. The first PID controller was tuned using the Ziegler-Nichols PID (ZN-PID) method, a classical empirical method that could yield poor performance in complex applications. The second PID controller utilizes a fuzzy inference system to dynamically adjust PID values (Fuzzy-PID). The performance of both controllers was evaluated in a MATLAB/Simulink model to demonstrate that the Fuzzy-PID controller significantly improves speed control accuracy and energy efficiency when controlling BLDC motors compared to the ZN-PID controller.