一类非线性离散时滞系统的启发式动态规划最优跟踪控制。

IEEE transactions on neural networks Pub Date : 2011-12-01 Epub Date: 2011-11-01 DOI:10.1109/TNN.2011.2172628
Huaguang Zhang, Ruizhuo Song, Qinglai Wei, Tieyan Zhang
{"title":"一类非线性离散时滞系统的启发式动态规划最优跟踪控制。","authors":"Huaguang Zhang,&nbsp;Ruizhuo Song,&nbsp;Qinglai Wei,&nbsp;Tieyan Zhang","doi":"10.1109/TNN.2011.2172628","DOIUrl":null,"url":null,"abstract":"<p><p>In this paper, a novel heuristic dynamic programming (HDP) iteration algorithm is proposed to solve the optimal tracking control problem for a class of nonlinear discrete-time systems with time delays. The novel algorithm contains state updating, control policy iteration, and performance index iteration. To get the optimal states, the states are also updated. Furthermore, the \"backward iteration\" is applied to state updating. Two neural networks are used to approximate the performance index function and compute the optimal control policy for facilitating the implementation of HDP iteration algorithm. At last, we present two examples to demonstrate the effectiveness of the proposed HDP iteration algorithm.</p>","PeriodicalId":13434,"journal":{"name":"IEEE transactions on neural networks","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TNN.2011.2172628","citationCount":"172","resultStr":"{\"title\":\"Optimal tracking control for a class of nonlinear discrete-time systems with time delays based on heuristic dynamic programming.\",\"authors\":\"Huaguang Zhang,&nbsp;Ruizhuo Song,&nbsp;Qinglai Wei,&nbsp;Tieyan Zhang\",\"doi\":\"10.1109/TNN.2011.2172628\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>In this paper, a novel heuristic dynamic programming (HDP) iteration algorithm is proposed to solve the optimal tracking control problem for a class of nonlinear discrete-time systems with time delays. The novel algorithm contains state updating, control policy iteration, and performance index iteration. To get the optimal states, the states are also updated. Furthermore, the \\\"backward iteration\\\" is applied to state updating. Two neural networks are used to approximate the performance index function and compute the optimal control policy for facilitating the implementation of HDP iteration algorithm. At last, we present two examples to demonstrate the effectiveness of the proposed HDP iteration algorithm.</p>\",\"PeriodicalId\":13434,\"journal\":{\"name\":\"IEEE transactions on neural networks\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1109/TNN.2011.2172628\",\"citationCount\":\"172\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE transactions on neural networks\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TNN.2011.2172628\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2011/11/1 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE transactions on neural networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TNN.2011.2172628","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2011/11/1 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 172

摘要

针对一类非线性离散时滞系统的最优跟踪控制问题,提出了一种新的启发式动态规划(HDP)迭代算法。该算法包含状态更新、控制策略迭代和性能指标迭代。为了获得最佳状态,状态也会被更新。此外,将“向后迭代”应用于状态更新。利用两个神经网络逼近性能指标函数,计算最优控制策略,便于HDP迭代算法的实现。最后,通过两个算例验证了所提出的HDP迭代算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimal tracking control for a class of nonlinear discrete-time systems with time delays based on heuristic dynamic programming.

In this paper, a novel heuristic dynamic programming (HDP) iteration algorithm is proposed to solve the optimal tracking control problem for a class of nonlinear discrete-time systems with time delays. The novel algorithm contains state updating, control policy iteration, and performance index iteration. To get the optimal states, the states are also updated. Furthermore, the "backward iteration" is applied to state updating. Two neural networks are used to approximate the performance index function and compute the optimal control policy for facilitating the implementation of HDP iteration algorithm. At last, we present two examples to demonstrate the effectiveness of the proposed HDP iteration algorithm.

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
IEEE transactions on neural networks
IEEE transactions on neural networks 工程技术-工程:电子与电气
自引率
0.00%
发文量
2
审稿时长
8.7 months
×
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