Grey wolf optimization-based improved closed-loop speed control for a BLDC motor drive

Abstract

Brushless DC motor (BLDC) is increasingly being used in many practical applications, and the speed tracking performance of closed-loop control has been an important issue for high-performance applications. In spite of many available nonlinear and adaptive controllers, the PID controller is still being used as speed controller because of its simple structure and easy to implement. However, the tuning of PID gains is a tedious process to achieve the desired performance. This paper focuses on the design of speed controller, and tuning its gains is grey wolf optimization. An objective function is formulated based on integral square error of speed error so as to improve the transient and steady-state performance. The objective function is minimized using grey wolf optimization (GWO). The proposed idea is evaluated by simulating the system under various operating conditions, and further, the experimental results show the supremacy of the controller.