PSO Based PI Controller for BLDC Motor

Abstract

This work uses an Optimization Algorithm (PSO)-based controller to operate a BLDC motor. The rate of BLDC motors is controlled using a PSO-based controller that takes acceleration into consideration. Particle swarm optimization is used to find the proper PI controller parameters, Kp and Ki, based on the designed speed reference and response speed. Because of its long processing lifespan, large speed response, high efficiency, and superior speed vs. torque characteristics, BLDC motors are now widely employed in various industrial and automobile applications. The results show that the Particle swarm optimization controller can properly manage the BLDC motor's speed while maintaining the necessary response speed. This paper shows how to use MATLAB/Simulink to build an electrical motor model and monitor the success of a Motor drive controller with a Pi control – Particle swarm control scheme. The speed is managed by a PID Controller that is optimised using the PSO technique in the model described. BLDC motors have been widely employed in variable-speed applications of motor drives because they have a higher peak speed, a better torque-to-weight ratio, and a simpler structure.