Grey Wolf Optimizer Based PID Controller for Speed Control of BLDC Motor

A BLDC motor is superior to a brushed DC motor, as it replaces the mechanical commutation unit with an electronic one; hence improving the dynamic characteristics, efficiency and reducing the noise level marginally. Maximum BLDC motor drives use PID controller to control the speed of the machine; because it is simple in structure, relatively cheaper and exhibits good performance. But the main problem associated with PID controller is adjusting its parameters during implementation. In recent works, it has been observed that Particle Swarm Optimization (PSO) technique showed good performance in tuning PID controller. For this purpose, in this article, Grey Wolf Optimization (GWO) algorithm is introduced; which is used to optimally tune the PID controller parameters. The objective of this article is to compare the results obtained for tuning of PID controller based on of GWO and PSO technique and a conclusion has been derived that the proposed approach yields superior dynamic performance for BLDC motor.

Automated summary

The study compared the results of tuning PID controller parameters based on Grey Wolf Optimization and Particle Swarm Optimization techniques, and found that the Grey Wolf Optimization method performs better in improving the dynamic performance of BLDC motors.