{"title":"Investigation of consensus for nonlinear time-varying multiagent systems via data-driven techniques","authors":"Yuanshan Liu, Yude Xia","doi":"10.1016/j.ins.2025.122052","DOIUrl":null,"url":null,"abstract":"<div><div>This paper employs data-driven techniques to investigate the robustness control of leader-follower consensus in nonlinear discrete-time time-varying multiagent systems with fixed topology. Initially, pertinent symbolic definitions for sampled data are established, followed by an introduction to graph theory and system models. As data-driven algorithms necessitate linear systems, each nonlinear subsystem is linearized. Subsequently, distributed controllers are designed based on control principles to ensure multi-agent consensus. Additionally, the controller gain matrix is derived via a data-driven method, with its feasibility theoretically verified by solving nonlinear matrix inequalities. Finally, numerical simulations validate the efficacy of this approach for achieving robust leader-follower consensus control.</div></div>","PeriodicalId":51063,"journal":{"name":"Information Sciences","volume":"708 ","pages":"Article 122052"},"PeriodicalIF":8.1000,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Information Sciences","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0020025525001847","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"0","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
This paper employs data-driven techniques to investigate the robustness control of leader-follower consensus in nonlinear discrete-time time-varying multiagent systems with fixed topology. Initially, pertinent symbolic definitions for sampled data are established, followed by an introduction to graph theory and system models. As data-driven algorithms necessitate linear systems, each nonlinear subsystem is linearized. Subsequently, distributed controllers are designed based on control principles to ensure multi-agent consensus. Additionally, the controller gain matrix is derived via a data-driven method, with its feasibility theoretically verified by solving nonlinear matrix inequalities. Finally, numerical simulations validate the efficacy of this approach for achieving robust leader-follower consensus control.
期刊介绍：
Informatics and Computer Science Intelligent Systems Applications is an esteemed international journal that focuses on publishing original and creative research findings in the field of information sciences. We also feature a limited number of timely tutorial and surveying contributions.
Our journal aims to cater to a diverse audience, including researchers, developers, managers, strategic planners, graduate students, and anyone interested in staying up-to-date with cutting-edge research in information science, knowledge engineering, and intelligent systems. While readers are expected to share a common interest in information science, they come from varying backgrounds such as engineering, mathematics, statistics, physics, computer science, cell biology, molecular biology, management science, cognitive science, neurobiology, behavioral sciences, and biochemistry.
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