A leader-following consensus of multi-agent systems with actuator saturation and semi-Markov switching topologies.

IF 2.6 4区 工程技术 Q1 Mathematics Mathematical Biosciences and Engineering Pub Date : 2024-03-01 DOI:10.3934/mbe.2024217
Jiangtao Dai, Ge Guo
{"title":"A leader-following consensus of multi-agent systems with actuator saturation and semi-Markov switching topologies.","authors":"Jiangtao Dai, Ge Guo","doi":"10.3934/mbe.2024217","DOIUrl":null,"url":null,"abstract":"<p><p>The leader-following consensus (LFC) issue is investigated in this paper for multi-agent systems (MASs) subject to actuator saturation with semi-Markov switching topologies (SMST). A new consensus protocol is proposed by using a semi-Markov process to model the switching of network topologies. Compared to the traditional Markov switching topologies, the SMST is more general and practical because the transition rates are time-varying. By using the local sector conditions and a suitable Lyapunov-Krasovskii functional, some sufficient conditions are proposed such that the leaderfollowing mean-square consensus is locally achieved. Based on the derived sufficient conditions, an optimization problem is analyzed to determine the consensus feedback gains and to find a maximal estimate of the domain of consensus attraction (DOCA) of a closed-loop model. At the end, a numerical case is presented to verify the performance of the design method.</p>","PeriodicalId":49870,"journal":{"name":"Mathematical Biosciences and Engineering","volume":null,"pages":null},"PeriodicalIF":2.6000,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mathematical Biosciences and Engineering","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.3934/mbe.2024217","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Mathematics","Score":null,"Total":0}
引用次数: 0

Abstract

The leader-following consensus (LFC) issue is investigated in this paper for multi-agent systems (MASs) subject to actuator saturation with semi-Markov switching topologies (SMST). A new consensus protocol is proposed by using a semi-Markov process to model the switching of network topologies. Compared to the traditional Markov switching topologies, the SMST is more general and practical because the transition rates are time-varying. By using the local sector conditions and a suitable Lyapunov-Krasovskii functional, some sufficient conditions are proposed such that the leaderfollowing mean-square consensus is locally achieved. Based on the derived sufficient conditions, an optimization problem is analyzed to determine the consensus feedback gains and to find a maximal estimate of the domain of consensus attraction (DOCA) of a closed-loop model. At the end, a numerical case is presented to verify the performance of the design method.

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
具有执行器饱和和半马尔可夫开关拓扑的多代理系统的领导者-跟随共识。
本文研究了半马尔可夫切换拓扑(SMST)下受执行器饱和影响的多代理系统(MAS)的领导-跟随共识(LFC)问题。通过使用半马尔可夫过程来模拟网络拓扑的切换,提出了一种新的共识协议。与传统的马尔可夫开关拓扑相比,半马尔可夫开关拓扑更具通用性和实用性,因为其转换率是时变的。通过使用局部扇区条件和合适的 Lyapunov-Krasovskii 函数,提出了一些充分条件,从而在局部实现了领导者跟随均方共识。根据推导出的充分条件,分析了一个优化问题,以确定共识反馈增益,并找到闭环模型共识吸引域(DOCA)的最大估计值。最后,介绍了一个数值案例,以验证设计方法的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Mathematical Biosciences and Engineering
Mathematical Biosciences and Engineering 工程技术-数学跨学科应用
CiteScore
3.90
自引率
7.70%
发文量
586
审稿时长
>12 weeks
期刊介绍: Mathematical Biosciences and Engineering (MBE) is an interdisciplinary Open Access journal promoting cutting-edge research, technology transfer and knowledge translation about complex data and information processing. MBE publishes Research articles (long and original research); Communications (short and novel research); Expository papers; Technology Transfer and Knowledge Translation reports (description of new technologies and products); Announcements and Industrial Progress and News (announcements and even advertisement, including major conferences).
期刊最新文献
CTFusion: CNN-transformer-based self-supervised learning for infrared and visible image fusion. Video-based person re-identification with complementary local and global features using a graph transformer. Modeling free tumor growth: Discrete, continuum, and hybrid approaches to interpreting cancer development. Retraction notice to "A video images-aware knowledge extraction method for intelligent healthcare management of basketball players" [Mathematical Biosciences and Engineering 20(2) (2023) 1919-1937]. Improved optimizer with deep learning model for emotion detection and classification.
×
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