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.

无刷直流电动机优于有刷直流电动机，因为它用电子电动机取代了机械换向装置。因此改善了动态特性，效率并降低了噪声水平。最大的BLDC电机驱动器使用PID控制器来控制机器的速度。因为它结构简单，相对便宜并且具有良好的性能。但是与PID控制器相关的主要问题是在实施过程中调整其参数。在最近的工作中，已经观察到粒子群优化（PSO）技术在调节PID控制器方面显示出良好的性能。为此，在本文中，介绍了“灰狼优化”（GWO）算法。用于优化PID控制器参数。