基于人工神经网络控制器的DFIM速度控制

Brahim Dahhou, A. Bouraiou
{"title":"基于人工神经网络控制器的DFIM速度控制","authors":"Brahim Dahhou, A. Bouraiou","doi":"10.1109/ICAEE53772.2022.9961983","DOIUrl":null,"url":null,"abstract":"Nonlinear characteristics and parameters variation of the Doubly Fed Induction Motor (DFIM) posed a serious problem during operation. For this purpose, it is necessary to use control laws insensitive to variations in parameters, disturbances, and non-linarites. In this paper, a speed controller of a DFIM by the application of a PI controller based on Artificial Neural Network (ANN) is proposed. The results obtained with ANNPI are compared with AFLC-PI. This controller is then designed and trained online using a back propagation network algorithm. The performance of the proposed controller is adopted using Matlab / Simulink. Simulation results show a fast dynamic response and good performance in tracking speed and torque.","PeriodicalId":206584,"journal":{"name":"2022 2nd International Conference on Advanced Electrical Engineering (ICAEE)","volume":"191 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Speed Control Of DFIM Using Artificial Neural Network Controller\",\"authors\":\"Brahim Dahhou, A. Bouraiou\",\"doi\":\"10.1109/ICAEE53772.2022.9961983\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Nonlinear characteristics and parameters variation of the Doubly Fed Induction Motor (DFIM) posed a serious problem during operation. For this purpose, it is necessary to use control laws insensitive to variations in parameters, disturbances, and non-linarites. In this paper, a speed controller of a DFIM by the application of a PI controller based on Artificial Neural Network (ANN) is proposed. The results obtained with ANNPI are compared with AFLC-PI. This controller is then designed and trained online using a back propagation network algorithm. The performance of the proposed controller is adopted using Matlab / Simulink. Simulation results show a fast dynamic response and good performance in tracking speed and torque.\",\"PeriodicalId\":206584,\"journal\":{\"name\":\"2022 2nd International Conference on Advanced Electrical Engineering (ICAEE)\",\"volume\":\"191 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 2nd International Conference on Advanced Electrical Engineering (ICAEE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICAEE53772.2022.9961983\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 2nd International Conference on Advanced Electrical Engineering (ICAEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAEE53772.2022.9961983","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

双馈感应电动机的非线性特性和参数变化是其运行中的一个严重问题。为此,有必要使用对参数变化、干扰和非线性不敏感的控制律。本文提出了一种基于人工神经网络(ANN)的PI控制器的DFIM速度控制器。并与AFLC-PI进行了比较。然后使用反向传播网络算法设计并在线训练该控制器。利用Matlab / Simulink对该控制器的性能进行了验证。仿真结果表明,该方法动态响应快,具有良好的速度和转矩跟踪性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Speed Control Of DFIM Using Artificial Neural Network Controller
Nonlinear characteristics and parameters variation of the Doubly Fed Induction Motor (DFIM) posed a serious problem during operation. For this purpose, it is necessary to use control laws insensitive to variations in parameters, disturbances, and non-linarites. In this paper, a speed controller of a DFIM by the application of a PI controller based on Artificial Neural Network (ANN) is proposed. The results obtained with ANNPI are compared with AFLC-PI. This controller is then designed and trained online using a back propagation network algorithm. The performance of the proposed controller is adopted using Matlab / Simulink. Simulation results show a fast dynamic response and good performance in tracking speed and torque.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
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:604180095
Book学术官方微信