Whale Optimization Algorithm(WOA) Based Speed Control of BLDC Motor

Shubham Banerjee, Sarode Shiva Kumar, A. Alam
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Abstract

This paper aims at a comparative analysis between the implementation of a Proportional Integral(PI) controller using PSO(Particle Swarm Optimization) and WOA(Whale Optimization Algorithm) for speed regulation of a BLDC motor. The goal is to use the system mathematical model to lower the overall transient time and achieve the desired speed at the earliest for the closed-loop control of the machine. The BLDC motor modelled in Simulink was run using both the tuning algorithms, developed through MATLAB codes. Upon detailed comparison, it was observed that the WOA optimized PI control was successful in determining intricate gains (kp and ki values) within much lesser iterations and run-time than that of the control developed through Particle Swarm Optimization algorithm.
基于鲸鱼优化算法(WOA)的无刷直流电机速度控制
本文旨在比较分析采用粒子群优化算法(PSO)和鲸鱼优化算法(WOA)实现的比例积分(PI)控制器对无刷直流电机的调速。目标是利用系统的数学模型来降低总体暂态时间,并尽早达到机器闭环控制所需的速度。在Simulink中建模的无刷直流电机使用这两种调谐算法运行,并通过MATLAB代码开发。经过详细比较,发现WOA优化的PI控制比通过粒子群优化算法开发的控制在更少的迭代和运行时间内成功地确定了复杂的增益(kp和ki值)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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