{"title":"具有异步通信功能的合作-竞争网络上的多代理双方成群控制","authors":"Zhuangzhuang Ma;Lei Shi;Kai Chen;Jinliang Shao;Yuhua Cheng","doi":"10.1109/TSIPN.2024.3384817","DOIUrl":null,"url":null,"abstract":"In this contribution, the bipartite flocking control problem of a set of autonomous mobile agents over cooperation-competition networks is investigated. Two kinds of asynchronous communication scenarios are considered, where each agent communicates with the neighbors only at certain time instants determined by its own clock, but not at other time instants. In addition, each agent adjusts the control input at all time instants in the first asynchronous scenario, and adjusts the control input only at its communication time instants in the second asynchronous scenario. Nonlinear positive and negative weight functions are designed to describe the effect of the distance between agents on the cooperation/competition degree in real interaction scenarios, where the farther (closer) the distance, the weaker (stronger) the cooperation/competition degree. With the help of signed graph theory and sub-stochastic matrix, the dynamic models under different asynchronous scenarios are analyzed, and the algebraic conditions for achieving bipartite flocking control are established separately. At last, the effectiveness of algebraic conditions is verified through numerical simulations.","PeriodicalId":56268,"journal":{"name":"IEEE Transactions on Signal and Information Processing over Networks","volume":"10 ","pages":"460-472"},"PeriodicalIF":3.0000,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multi-Agent Bipartite Flocking Control Over Cooperation-Competition Networks With Asynchronous Communications\",\"authors\":\"Zhuangzhuang Ma;Lei Shi;Kai Chen;Jinliang Shao;Yuhua Cheng\",\"doi\":\"10.1109/TSIPN.2024.3384817\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this contribution, the bipartite flocking control problem of a set of autonomous mobile agents over cooperation-competition networks is investigated. Two kinds of asynchronous communication scenarios are considered, where each agent communicates with the neighbors only at certain time instants determined by its own clock, but not at other time instants. In addition, each agent adjusts the control input at all time instants in the first asynchronous scenario, and adjusts the control input only at its communication time instants in the second asynchronous scenario. Nonlinear positive and negative weight functions are designed to describe the effect of the distance between agents on the cooperation/competition degree in real interaction scenarios, where the farther (closer) the distance, the weaker (stronger) the cooperation/competition degree. With the help of signed graph theory and sub-stochastic matrix, the dynamic models under different asynchronous scenarios are analyzed, and the algebraic conditions for achieving bipartite flocking control are established separately. At last, the effectiveness of algebraic conditions is verified through numerical simulations.\",\"PeriodicalId\":56268,\"journal\":{\"name\":\"IEEE Transactions on Signal and Information Processing over Networks\",\"volume\":\"10 \",\"pages\":\"460-472\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2024-04-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Signal and Information Processing over Networks\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10490266/\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Signal and Information Processing over Networks","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10490266/","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Multi-Agent Bipartite Flocking Control Over Cooperation-Competition Networks With Asynchronous Communications
In this contribution, the bipartite flocking control problem of a set of autonomous mobile agents over cooperation-competition networks is investigated. Two kinds of asynchronous communication scenarios are considered, where each agent communicates with the neighbors only at certain time instants determined by its own clock, but not at other time instants. In addition, each agent adjusts the control input at all time instants in the first asynchronous scenario, and adjusts the control input only at its communication time instants in the second asynchronous scenario. Nonlinear positive and negative weight functions are designed to describe the effect of the distance between agents on the cooperation/competition degree in real interaction scenarios, where the farther (closer) the distance, the weaker (stronger) the cooperation/competition degree. With the help of signed graph theory and sub-stochastic matrix, the dynamic models under different asynchronous scenarios are analyzed, and the algebraic conditions for achieving bipartite flocking control are established separately. At last, the effectiveness of algebraic conditions is verified through numerical simulations.
期刊介绍:
The IEEE Transactions on Signal and Information Processing over Networks publishes high-quality papers that extend the classical notions of processing of signals defined over vector spaces (e.g. time and space) to processing of signals and information (data) defined over networks, potentially dynamically varying. In signal processing over networks, the topology of the network may define structural relationships in the data, or may constrain processing of the data. Topics include distributed algorithms for filtering, detection, estimation, adaptation and learning, model selection, data fusion, and diffusion or evolution of information over such networks, and applications of distributed signal processing.