Performance Enhancement of BLDC Motor Drive Systems Using Fuzzy Logic Control and PID Controller for Improved Transient Response and Stability

Currently, systems generally need control units, which requires designing them to analyze the behavior of the system when there are suitable characteristics of the motor according to the required application. The electric motor is very important in many applications and is widely used because of the high-efficiency mechanical power, small sizes, and relatively high torques that these electrical machines have. Improving the performance of systems requires control units, which are of the types of traditional PID, expert Fuzzy, and intelligent control systems. Two systems were proposed, a system that relies on a traditional control unit and a system that relies on fuzzy logic to improve and raise the efficiency of performance and handle system fluctuations resulting from disturbances and different operating conditions. Simulation tests were conducted using MATLAB. The effectiveness of the proposed controllers is evaluated through measurement criteria including efficiency improvements, torque ripple reduction, or settling time. Simulation results for both the closed-loop system using the conventional controller and the expert controller showed that the improvement in system performance can be determined according to criteria that include response speed as well as the overshoot and undershoot rates. Specifically, the settling time using the conventional controller was 3.05 msec. The rise time using the conventional controller was 205.406 msec, while using the expert controller it was 205.406 msec. The overshoot rate (%) using the conventional controller was 18.452%, while using the expert controller it was 6.989%. The undershoot rate using the conventional controller was 6.633%, while using the expert controller it was 1.987%.