A synchronous generator fuzzy excitation controller optimally designed with a genetic algorithm

J. Wen, Shijie Cheng, O. Malik
{"title":"A synchronous generator fuzzy excitation controller optimally designed with a genetic algorithm","authors":"J. Wen, Shijie Cheng, O. Malik","doi":"10.1109/PICA.1997.599384","DOIUrl":null,"url":null,"abstract":"Design of a fuzzy logic power system controller with satisfactory performance is not an easy task. The difficulties come from two aspects. First, design of a fuzzy logic computer mainly uses the experience of the human experts. To acquire enough heuristic knowledge from the domain experts and to represent this kind of knowledge appropriately with a set of fuzzy rules presents difficulties. Second, it is difficult to appropriately tune the parameters used in the fuzzy logic controller. These parameters are commonly determined by a \"trial and error\" method which is rather time consuming. In this paper, a genetic algorithm is introduced to design an optimal fuzzy logic controller. The proposed method has been used to design an optimal fuzzy logic excitation controller for a generating unit. Test results with the fuzzy logic controller show very satisfactory results.","PeriodicalId":383749,"journal":{"name":"Proceedings of the 20th International Conference on Power Industry Computer Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"66","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 20th International Conference on Power Industry Computer Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PICA.1997.599384","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 66

Abstract

Design of a fuzzy logic power system controller with satisfactory performance is not an easy task. The difficulties come from two aspects. First, design of a fuzzy logic computer mainly uses the experience of the human experts. To acquire enough heuristic knowledge from the domain experts and to represent this kind of knowledge appropriately with a set of fuzzy rules presents difficulties. Second, it is difficult to appropriately tune the parameters used in the fuzzy logic controller. These parameters are commonly determined by a "trial and error" method which is rather time consuming. In this paper, a genetic algorithm is introduced to design an optimal fuzzy logic controller. The proposed method has been used to design an optimal fuzzy logic excitation controller for a generating unit. Test results with the fuzzy logic controller show very satisfactory results.
采用遗传算法优化设计了同步发电机模糊励磁控制器
设计一个性能满意的模糊逻辑电力系统控制器不是一件容易的事情。困难来自两个方面。首先,模糊逻辑计算机的设计主要利用了人类专家的经验。如何从领域专家那里获得足够的启发式知识,并用一套模糊规则来恰当地表示这些知识是一个难点。其次,模糊控制器中使用的参数难以适当调整。这些参数通常是通过“试错法”确定的,这种方法相当耗时。本文引入遗传算法来设计最优模糊控制器。该方法已应用于某发电机组模糊逻辑励磁控制器的优化设计。用模糊控制器进行测试,取得了令人满意的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信