Comparison on the performance of Induction motor control using fuzzy and ANFIS controllers

R. Simon, A. Geetha
{"title":"Comparison on the performance of Induction motor control using fuzzy and ANFIS controllers","authors":"R. Simon, A. Geetha","doi":"10.1109/ICE-CCN.2013.6528549","DOIUrl":null,"url":null,"abstract":"This paper presents the fuzzy and ANFIS control system for Induction motor drives for better performance. The design and simulation of fuzzy logic controller and ANFIS for Induction motor are carried out based on fuzzy set theory and Back propagation. Fuzzy Controller will produce the output based on the rules provided and that are based on human experience. Whereas ANFIS is a best tradeoff between neural and fuzzy system which provide smoothness, due to the fuzzy controller (FC) interpolation and adaptability due to the neural network (NN) Back propagation. Simulated result for Fuzzy and ANFIS controlled Induction motor shows that latter exhibit better results.","PeriodicalId":286830,"journal":{"name":"2013 IEEE International Conference ON Emerging Trends in Computing, Communication and Nanotechnology (ICECCN)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE International Conference ON Emerging Trends in Computing, Communication and Nanotechnology (ICECCN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICE-CCN.2013.6528549","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8

Abstract

This paper presents the fuzzy and ANFIS control system for Induction motor drives for better performance. The design and simulation of fuzzy logic controller and ANFIS for Induction motor are carried out based on fuzzy set theory and Back propagation. Fuzzy Controller will produce the output based on the rules provided and that are based on human experience. Whereas ANFIS is a best tradeoff between neural and fuzzy system which provide smoothness, due to the fuzzy controller (FC) interpolation and adaptability due to the neural network (NN) Back propagation. Simulated result for Fuzzy and ANFIS controlled Induction motor shows that latter exhibit better results.
采用模糊控制器和ANFIS控制器控制感应电机的性能比较
本文提出了一种基于模糊神经网络的感应电机驱动控制系统。基于模糊集理论和反向传播理论,对异步电动机的模糊逻辑控制器和ANFIS进行了设计和仿真。模糊控制器将根据所提供的规则和基于人类经验的规则产生输出。然而,由于模糊控制器(FC)的插值和神经网络(NN)反向传播的自适应性,ANFIS是神经和模糊系统之间的最佳折衷,提供了平滑性。对模糊控制和ANFIS控制异步电动机的仿真结果表明,后者具有更好的控制效果。
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