Variable loaded brushless DC motor with six step commutation PID-based speed controller optimized by PSO algorithm

Abstract

This research presents a method for regulating varying voltage as a DC source in a six-step commutation brushless DC (BLDC) motor drive through control proportional integral derivative (PID) as a simple strategy for controlling the speed of BLDC motors. Strengthening the control gain uses the particle swarm optimization (PSO) algorithm by minimizing the root mean square error (RMSE) and overshoot as fitness control characteristics. The performance of the motor with the proposed controller is analyzed and compared with an experimentally-simulated-tuned PID, hybrid gray wolf optimization–proportional integral (GWO-PI), and hybrid horse herd PSO-PID (HHH PSO-PID) under changing load and speed conditions. Simulation using compose-psim altair software. Control system response parameters such as RMSE, overshoot, electromagnetic torque ripple, and phase current ripple are measured and compared with the above controllers. The results show that the proposed controller is superior to a wide range of predefined system responses.