{"title":"Leader-Following Consensus With Prescribed Time-Bound and Order of Multiagent Systems With Increasing Scales: A Chain-Patterned Approach.","authors":"Nengneng Qing,Xiaoli Luan,Fei Liu","doi":"10.1109/tcyb.2025.3616239","DOIUrl":null,"url":null,"abstract":"A chain-patterned approach is proposed to achieve the novel leader-following consensus (LFC) with prescribed time-bound and order for MAS under directed chain interaction with increasing scales. Using chain-patterned polynomial encodings, this approach confines all effects of scale variation, thereby accommodating increasing scales without requiring prior knowledge of every interaction at all open moments, like the existing studies. Moreover, TBBG are embedded in this approach to guarantee the novel LFC with prescribed time and bound, while avoiding the infinity-approaching time-varying parameters. Furthermore, the important property order is further enforced and obtained under the proposed approach, conforming to the unidirectional information flow characteristic of chains. Finally, the validity and superiority of the proposed chain-patterned approach are demonstrated by comparative examples.","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"111 1","pages":""},"PeriodicalIF":10.5000,"publicationDate":"2025-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Cybernetics","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1109/tcyb.2025.3616239","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
A chain-patterned approach is proposed to achieve the novel leader-following consensus (LFC) with prescribed time-bound and order for MAS under directed chain interaction with increasing scales. Using chain-patterned polynomial encodings, this approach confines all effects of scale variation, thereby accommodating increasing scales without requiring prior knowledge of every interaction at all open moments, like the existing studies. Moreover, TBBG are embedded in this approach to guarantee the novel LFC with prescribed time and bound, while avoiding the infinity-approaching time-varying parameters. Furthermore, the important property order is further enforced and obtained under the proposed approach, conforming to the unidirectional information flow characteristic of chains. Finally, the validity and superiority of the proposed chain-patterned approach are demonstrated by comparative examples.
期刊介绍:
The scope of the IEEE Transactions on Cybernetics includes computational approaches to the field of cybernetics. Specifically, the transactions welcomes papers on communication and control across machines or machine, human, and organizations. The scope includes such areas as computational intelligence, computer vision, neural networks, genetic algorithms, machine learning, fuzzy systems, cognitive systems, decision making, and robotics, to the extent that they contribute to the theme of cybernetics or demonstrate an application of cybernetics principles.