{"title":"随机多智能体系统的自适应预定义时间一致性控制","authors":"Guanli Xiao, Lulu Ren, Quanxin Zhu, JinRong Wang","doi":"10.1002/rnc.70014","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>This paper aims to study the adaptive predefined-time consensus control for stochastic multi-agent systems (SMASs). First, the classic Bihari's inequality has been extended and a Lyapunov theorem on predefined-time stability for nonlinear stochastic systems is established. Second, a distributed predefined-time consensus protocol is proposed for SMASs by leveraging the adaptive techniques. It is worth emphasizing that the proof of the validity of the control protocol is based on the predefined-time stability that we have established. Finally, an example is given to verify the main results.</p>\n </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"35 15","pages":"6534-6544"},"PeriodicalIF":3.2000,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Adaptive Predefined-Time Consensus Control for Stochastic Multi-Agent Systems\",\"authors\":\"Guanli Xiao, Lulu Ren, Quanxin Zhu, JinRong Wang\",\"doi\":\"10.1002/rnc.70014\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n <p>This paper aims to study the adaptive predefined-time consensus control for stochastic multi-agent systems (SMASs). First, the classic Bihari's inequality has been extended and a Lyapunov theorem on predefined-time stability for nonlinear stochastic systems is established. Second, a distributed predefined-time consensus protocol is proposed for SMASs by leveraging the adaptive techniques. It is worth emphasizing that the proof of the validity of the control protocol is based on the predefined-time stability that we have established. Finally, an example is given to verify the main results.</p>\\n </div>\",\"PeriodicalId\":50291,\"journal\":{\"name\":\"International Journal of Robust and Nonlinear Control\",\"volume\":\"35 15\",\"pages\":\"6534-6544\"},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2025-06-11\",\"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.70014\",\"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.70014","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}
Adaptive Predefined-Time Consensus Control for Stochastic Multi-Agent Systems
This paper aims to study the adaptive predefined-time consensus control for stochastic multi-agent systems (SMASs). First, the classic Bihari's inequality has been extended and a Lyapunov theorem on predefined-time stability for nonlinear stochastic systems is established. Second, a distributed predefined-time consensus protocol is proposed for SMASs by leveraging the adaptive techniques. It is worth emphasizing that the proof of the validity of the control protocol is based on the predefined-time stability that we have established. Finally, an example is given to verify the main results.
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.