Synchronous generator excitation system optimization control based on multi-Agent genetic algorithm

被引：0
作者：
Cheng, Ruofa [1 ,2 ]
Gao, Jianchao [1 ]
Yu, Xinhong [1 ]
Deng, Hongfeng [1 ]
机构：
[1] Nanchang Hangkong University, 330063, Nanchang
[2] School of Information Engineering, Nanchang Hangkong University, Nanchang, Jiangxi
来源：
Information Technology Journal | 2013年 / 12卷 / 19期
关键词：
CMAC controller; Excitation controller; Multi-Agent genetic algorithm; PID controller; Synchronous generator;
D O I：
10.3923/itj.2013.4959.4967
中图分类号：
学科分类号：
摘要：
Excitation control system of synchronous generator is a strong nonlineariry, multi-variable, strong couple and time-varying control system. It is very difficult for traditional Proportional Integral Derivative (PID) to get good control performance. A new excitation control strategy based on PID controller and Cerebellar Model Articulation Controller (CMAC) is proposed in this study. To solve the problem of PID and CMAC compound controller multi-parameter setting, an Improved Multi-Agent Genetic Algorithm (IMAGA) is presented. The PID parameters Kp, Ki, Kd and CMAC parameters T|, a are regarded as a agent. Each agent continuously improves its fitness value through competition and cooperation between the other agents according to the objective function of Integral of Time-weighted Absolute value of the Error (ITAE). This algorithm adopts multi-Agent coordinate optimization to realize the five parameters of Kp, Ki, Kd, r, aonline tuning. The simulations results show that the compound control scheme based on multi-Agent genetic algorithm can improve the precision of excitation control, the speed of responding and has better dynamic and steady-state characteristics. © 2013 Asian Network for Scientific Information.
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页码：4959 / 4967
页数：8
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