{"title":"Consensus of High-Order Multiagent Systems With Binary-Valued Communications and Switching Topologies","authors":"Ru An;Ying Wang;Yanlong Zhao;Ji-Feng Zhang","doi":"10.1109/TCNS.2024.3516582","DOIUrl":null,"url":null,"abstract":"This article studies the consensus problem of high-order multiagent systems (MASs) with binary-valued communications and switching topologies. To tackle the challenge of unknown states caused by binary-valued communications, this article constructs an estimation-based consensus algorithm. First, a recursive projection identification algorithm is presented to estimate the neighbors' states dynamically. Then, based on these estimates, a consensus law is designed. By constructing and analyzing two combined Lyapunov functions about estimation error and state error, this article establishes their relation to overcome the difficulty resulting from the coupling of the estimation and control and less information due to switching topologies. Under the condition of jointly connected topologies, it is proven that by properly selecting the step coefficient, the estimates of states can converge to the true states with a convergence rate as the reciprocal of the recursion times. Besides, the MAS is proved to achieve weak consensus and the consensus rate is also established as the reciprocal of the recursion times. Finally, a simulation example is given to validate the algorithm.","PeriodicalId":56023,"journal":{"name":"IEEE Transactions on Control of Network Systems","volume":"12 2","pages":"1369-1380"},"PeriodicalIF":4.0000,"publicationDate":"2024-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Control of Network Systems","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10795218/","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}
引用次数: 0
Abstract
This article studies the consensus problem of high-order multiagent systems (MASs) with binary-valued communications and switching topologies. To tackle the challenge of unknown states caused by binary-valued communications, this article constructs an estimation-based consensus algorithm. First, a recursive projection identification algorithm is presented to estimate the neighbors' states dynamically. Then, based on these estimates, a consensus law is designed. By constructing and analyzing two combined Lyapunov functions about estimation error and state error, this article establishes their relation to overcome the difficulty resulting from the coupling of the estimation and control and less information due to switching topologies. Under the condition of jointly connected topologies, it is proven that by properly selecting the step coefficient, the estimates of states can converge to the true states with a convergence rate as the reciprocal of the recursion times. Besides, the MAS is proved to achieve weak consensus and the consensus rate is also established as the reciprocal of the recursion times. Finally, a simulation example is given to validate the algorithm.
期刊介绍:
The IEEE Transactions on Control of Network Systems is committed to the timely publication of high-impact papers at the intersection of control systems and network science. In particular, the journal addresses research on the analysis, design and implementation of networked control systems, as well as control over networks. Relevant work includes the full spectrum from basic research on control systems to the design of engineering solutions for automatic control of, and over, networks. The topics covered by this journal include: Coordinated control and estimation over networks, Control and computation over sensor networks, Control under communication constraints, Control and performance analysis issues that arise in the dynamics of networks used in application areas such as communications, computers, transportation, manufacturing, Web ranking and aggregation, social networks, biology, power systems, economics, Synchronization of activities across a controlled network, Stability analysis of controlled networks, Analysis of networks as hybrid dynamical systems.