Fuzzy RBF neural network in the application of magnetic levitation system

Jing Zhang, Sai Dai, Jiamin Li, Ning Wang
{"title":"Fuzzy RBF neural network in the application of magnetic levitation system","authors":"Jing Zhang, Sai Dai, Jiamin Li, Ning Wang","doi":"10.1109/IFOST.2011.6021187","DOIUrl":null,"url":null,"abstract":"To solve the problems that magnetic levitation system has the characteristics of open-loop instability and nonlinearity and the traditional PID controller is difficult to achieve good control effect because of the fixed parameters, a kind of intelligent PID control system based on fuzzy RBF neural network is proposed in this paper. This method combines the reasoning ability of fuzzy control with study ability of neural network. Fuzzy control and RBF neural network are applied in order to adjust the parameters of PID kp, ki and kd online which is to satisfy the static and dynamic performance requirements in magnetic levitation system. By comparing with the conventional PID control, the results showed that, the improved control has better adaptability and robustness which can control magnetic levitation system more effectively.","PeriodicalId":20466,"journal":{"name":"Proceedings of 2011 6th International Forum on Strategic Technology","volume":"13 1","pages":"990-994"},"PeriodicalIF":0.0000,"publicationDate":"2011-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 2011 6th International Forum on Strategic Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IFOST.2011.6021187","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

To solve the problems that magnetic levitation system has the characteristics of open-loop instability and nonlinearity and the traditional PID controller is difficult to achieve good control effect because of the fixed parameters, a kind of intelligent PID control system based on fuzzy RBF neural network is proposed in this paper. This method combines the reasoning ability of fuzzy control with study ability of neural network. Fuzzy control and RBF neural network are applied in order to adjust the parameters of PID kp, ki and kd online which is to satisfy the static and dynamic performance requirements in magnetic levitation system. By comparing with the conventional PID control, the results showed that, the improved control has better adaptability and robustness which can control magnetic levitation system more effectively.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
模糊RBF神经网络在磁悬浮系统中的应用
针对磁悬浮系统具有开环不稳定性和非线性的特点,以及传统PID控制器由于参数固定而难以达到良好控制效果的问题,提出了一种基于模糊RBF神经网络的智能PID控制系统。该方法将模糊控制的推理能力与神经网络的学习能力相结合。采用模糊控制和RBF神经网络对PID kp、ki和kd的参数进行在线调节,以满足磁悬浮系统的静态和动态性能要求。与传统的PID控制相比,改进后的PID控制具有更好的自适应性和鲁棒性,可以更有效地控制磁悬浮系统。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Crack-healing behavior of Al2O3/SiC composite Characterization of nanopowders produced by electrical explosion of titanium wires Design of fuzzy logic controller for two-wheeled self-balancing robot The design of the network video terminals based on embedded QT Theoretical calculation and numerical simulation of spherical lung cancer cells' refractive index
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1