约束比特率下非线性多智能体系统的无模型自适应控制:一种编解码机制

IF 3.2 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS
Shanshan Zheng, Shuai Liu, Licheng Wang
{"title":"约束比特率下非线性多智能体系统的无模型自适应控制:一种编解码机制","authors":"Shanshan Zheng,&nbsp;Shuai Liu,&nbsp;Licheng Wang","doi":"10.1002/rnc.8003","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>In this article, the model-free-based consensus tracking control problem is investigated for nonlinear discrete-time multi-agent systems (MASs) subject to constrained bit rate. A dynamic linearization technology is employed, by which the original unknown nonlinear system is equivalently transformed into a dynamic linearized model. An encoding-decoding mechanism (EDM) is applied to encode the measurement outputs into the binary codewords with fewer occupations of the network bandwidth. On this basis, a distributed model-free adaptive control (MFAC) scheme is developed, while sufficient conditions are presented to ensure that the close-loop MAS achieves the expected consensus performance. The proposed scheme is completely data-driven without relying on any information from the system model or structure. Meanwhile, the inherent relationship between bit rate constraints and decoding accuracy is revealed. Finally, simulation results are presented to demonstrate the validity of the provided approach.</p>\n </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"35 13","pages":"5600-5610"},"PeriodicalIF":3.2000,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Model-Free Adaptive Control for Nonlinear Multi-Agent Systems Under Constrained Bit Rate: An Encoding-Decoding Mechanism\",\"authors\":\"Shanshan Zheng,&nbsp;Shuai Liu,&nbsp;Licheng Wang\",\"doi\":\"10.1002/rnc.8003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n <p>In this article, the model-free-based consensus tracking control problem is investigated for nonlinear discrete-time multi-agent systems (MASs) subject to constrained bit rate. A dynamic linearization technology is employed, by which the original unknown nonlinear system is equivalently transformed into a dynamic linearized model. An encoding-decoding mechanism (EDM) is applied to encode the measurement outputs into the binary codewords with fewer occupations of the network bandwidth. On this basis, a distributed model-free adaptive control (MFAC) scheme is developed, while sufficient conditions are presented to ensure that the close-loop MAS achieves the expected consensus performance. The proposed scheme is completely data-driven without relying on any information from the system model or structure. Meanwhile, the inherent relationship between bit rate constraints and decoding accuracy is revealed. Finally, simulation results are presented to demonstrate the validity of the provided approach.</p>\\n </div>\",\"PeriodicalId\":50291,\"journal\":{\"name\":\"International Journal of Robust and Nonlinear Control\",\"volume\":\"35 13\",\"pages\":\"5600-5610\"},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2025-04-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Robust and Nonlinear Control\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/rnc.8003\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Robust and Nonlinear Control","FirstCategoryId":"94","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/rnc.8003","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
引用次数: 0

摘要

研究了具有约束比特率的非线性离散多智能体系统的无模型一致性跟踪控制问题。采用动态线性化技术,将原未知非线性系统等效转化为动态线性化模型。采用编解码机制(EDM)将测量输出编码成占用较少网络带宽的二进制码字。在此基础上,提出了分布式无模型自适应控制(MFAC)方案,并给出了保证闭环MAS达到预期共识性能的充分条件。提出的方案完全是数据驱动的,不依赖于任何来自系统模型或结构的信息。同时,揭示了码率约束与解码精度之间的内在关系。最后给出了仿真结果,验证了所提方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Model-Free Adaptive Control for Nonlinear Multi-Agent Systems Under Constrained Bit Rate: An Encoding-Decoding Mechanism

In this article, the model-free-based consensus tracking control problem is investigated for nonlinear discrete-time multi-agent systems (MASs) subject to constrained bit rate. A dynamic linearization technology is employed, by which the original unknown nonlinear system is equivalently transformed into a dynamic linearized model. An encoding-decoding mechanism (EDM) is applied to encode the measurement outputs into the binary codewords with fewer occupations of the network bandwidth. On this basis, a distributed model-free adaptive control (MFAC) scheme is developed, while sufficient conditions are presented to ensure that the close-loop MAS achieves the expected consensus performance. The proposed scheme is completely data-driven without relying on any information from the system model or structure. Meanwhile, the inherent relationship between bit rate constraints and decoding accuracy is revealed. Finally, simulation results are presented to demonstrate the validity of the provided approach.

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
International Journal of Robust and Nonlinear Control
International Journal of Robust and Nonlinear Control 工程技术-工程:电子与电气
CiteScore
6.70
自引率
20.50%
发文量
505
审稿时长
2.7 months
期刊介绍: Papers that do not include an element of robust or nonlinear control and estimation theory will not be considered by the journal, and all papers will be expected to include significant novel content. The focus of the journal is on model based control design approaches rather than heuristic or rule based methods. Papers on neural networks will have to be of exceptional novelty to be considered for the journal.
×
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