Active Disturbance Rejection Control of Certain Balanced and Positioning Electro-Hydraulic Servo System Based on Neural Network

Litong Jia, Q. Gao, Yuan-long Hou, Zhiyuan Jia, L. Jin, Kang Li
{"title":"Active Disturbance Rejection Control of Certain Balanced and Positioning Electro-Hydraulic Servo System Based on Neural Network","authors":"Litong Jia, Q. Gao, Yuan-long Hou, Zhiyuan Jia, L. Jin, Kang Li","doi":"10.1109/IHMSC.2015.207","DOIUrl":null,"url":null,"abstract":"For certain balance and positioning of electro-hydraulic servo system existing nonlinear, the active disturbance rejection control (ADRC) has many adjustable parameters which are difficult to regulate, so active disturbance rejection control with neural network (NN-ADRC) is developed in this paper. The method uses neural network self-learning ability, through a single neuron adaptive configuration parameters to complete an online self-tuning parameters, while taking advantage of RBF neural network as identifier to identify the controlled object gradient information. Simulation results show that: the controller parameters are reduced significantly, and effectively inhibit the system unbalance force disturbance and realize the accurate positioning. It also has fast response speed, no overshoot, and high steady-state accuracy.","PeriodicalId":6592,"journal":{"name":"2015 7th International Conference on Intelligent Human-Machine Systems and Cybernetics","volume":"20 1","pages":"211-215"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 7th International Conference on Intelligent Human-Machine Systems and Cybernetics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IHMSC.2015.207","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

For certain balance and positioning of electro-hydraulic servo system existing nonlinear, the active disturbance rejection control (ADRC) has many adjustable parameters which are difficult to regulate, so active disturbance rejection control with neural network (NN-ADRC) is developed in this paper. The method uses neural network self-learning ability, through a single neuron adaptive configuration parameters to complete an online self-tuning parameters, while taking advantage of RBF neural network as identifier to identify the controlled object gradient information. Simulation results show that: the controller parameters are reduced significantly, and effectively inhibit the system unbalance force disturbance and realize the accurate positioning. It also has fast response speed, no overshoot, and high steady-state accuracy.
基于神经网络的平衡定位电液伺服系统自抗扰控制
针对电液伺服系统存在一定的非线性平衡和定位问题,提出了一种基于神经网络的自抗扰控制方法(NN-ADRC)。该方法利用神经网络的自学习能力,通过单个神经元自适应配置参数来完成参数的在线自整定,同时利用RBF神经网络作为辨识器来识别被控对象的梯度信息。仿真结果表明:控制器参数明显减小,有效抑制了系统不平衡力扰动,实现了精确定位。响应速度快,无超调,稳态精度高。
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