基于灰狼优化算法的AVR电力系统PID控制器设计

Rvindra kumar Kuri, D. Paliwal, D. K. Sambariya
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引用次数: 6

摘要

针对给定的自动调压系统(AVR),提出了一种基于迁移行为的灰狼优化算法(GWO),以获得PID控制器的最优值。在本文中,我们简要描述了灰狼优化算法的细节,以适当兼容PID控制器的参数与积分平方误差(ISE)利用目标函数。本文提出的AVR响应的课题仿真结果与灰狼优化(GWO)、水循环算法(WCA)、帝王蝴蝶算法(MBA)、粒子群优化(PSO)、混沌粒子群优化(CPSO)算法在峰值时间、振幅和稳定时间方面基本一致,并对包括IAE、ISE和ITAE函数在内的性能进行了检验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Grey Wolf Optimization Algorithm based PID controller design for AVR Power system
This Article deals with grey wolf optimization algorithm (GWO) detestable on migration demeanors proposed to get the optimum values implementing PID controller for a given automatic voltage regulator system (AVR). In this paper, we briefly described the details about the grey wolf optimization algorithm for proper compatibility of the parameters of PID controllers with integral square error (ISE) using the objective function. the proposed topic simulation outcomes of the response of AVR assimilate with Grey wolf Optimization (GWO), Water Cycle Algorithm (WCA), Monarch butterfly algorithm (MBA), Particle Swarm Optimization (PSO), Chaotic PSO(CPSO), algorithm in terms of peak time, amplitude and settling time with performance check including IAE, ISE, and ITAE function.
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