{"title":"Formation control of multiagent systems with multileaders through completely distributed intermittent communication strategies","authors":"Jian Feng , Weizhao Song , Lijuan Xu , Juan Zhang","doi":"10.1016/j.ins.2024.121555","DOIUrl":null,"url":null,"abstract":"<div><div>The distributed time-varying formation (TVF) control problem of multiagent systems (MASs) with multileaders is explored in this research. Contrasted with the existing results, this paper considers the following situations: 1) the multifollower group is heterogeneous, as is the multileader group; 2) the heterogeneous system matrices of the multileaders are not already known to all followers; 3) some strict constraint conditions, such as well-informed follower assumption and virtual leader condition, are removed. This paper presents the event-triggered (ET) matrix observer, the adaptive ET state compensator, and the output-feedback TVF controller, which are constituted as the innovative completely distributed ET control protocol. Considering the limited communication bandwidth, the ET matrix observer and compensator are designed, with the communication-bandwidth-saving manners, to estimate the integrated system matrix and integrated state information of all leader agents, respectively. The output feedback formation controller is built to adjust the followers to keep the predetermined team formations and follow the reference trace, where the trace is all leaders outputs' convex combination. The stability analysis and simulation experiment are brought out to demonstrate the validity of the suggested control strategy.</div></div>","PeriodicalId":51063,"journal":{"name":"Information Sciences","volume":"690 ","pages":"Article 121555"},"PeriodicalIF":8.1000,"publicationDate":"2024-10-18","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/S0020025524014695","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
The distributed time-varying formation (TVF) control problem of multiagent systems (MASs) with multileaders is explored in this research. Contrasted with the existing results, this paper considers the following situations: 1) the multifollower group is heterogeneous, as is the multileader group; 2) the heterogeneous system matrices of the multileaders are not already known to all followers; 3) some strict constraint conditions, such as well-informed follower assumption and virtual leader condition, are removed. This paper presents the event-triggered (ET) matrix observer, the adaptive ET state compensator, and the output-feedback TVF controller, which are constituted as the innovative completely distributed ET control protocol. Considering the limited communication bandwidth, the ET matrix observer and compensator are designed, with the communication-bandwidth-saving manners, to estimate the integrated system matrix and integrated state information of all leader agents, respectively. The output feedback formation controller is built to adjust the followers to keep the predetermined team formations and follow the reference trace, where the trace is all leaders outputs' convex combination. The stability analysis and simulation experiment are brought out to demonstrate the validity of the suggested control strategy.
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.