{"title":"Controller and topology co-optimization for consensus of multi-agent systems","authors":"Luyao Wang, Baofeng Zhang, Dan Ma","doi":"10.1109/YAC.2018.8406455","DOIUrl":null,"url":null,"abstract":"In this paper, the co-optimization problem between controller and topology for consensus of multi-agent systems is investigated. Firstly, the distributed control protocol for consensus of multi-agent systems is optimized for the given quadratic performance index. The proposed optimal controller depends on the Laplace matrix of the topological graph. Secondly, in order to further reduce the communication energy of the topology, but not affect the convergence speed of multi-agent systems, the topology optimization algorithm and the eigenvalue optimization method for multi-agent systems are presented, which balances the communication energy and control energy of the systems. Finally, the simulation results show that the topology optimization based on the controller optimization is able to improve the system performance.","PeriodicalId":226586,"journal":{"name":"2018 33rd Youth Academic Annual Conference of Chinese Association of Automation (YAC)","volume":"263 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 33rd Youth Academic Annual Conference of Chinese Association of Automation (YAC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/YAC.2018.8406455","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, the co-optimization problem between controller and topology for consensus of multi-agent systems is investigated. Firstly, the distributed control protocol for consensus of multi-agent systems is optimized for the given quadratic performance index. The proposed optimal controller depends on the Laplace matrix of the topological graph. Secondly, in order to further reduce the communication energy of the topology, but not affect the convergence speed of multi-agent systems, the topology optimization algorithm and the eigenvalue optimization method for multi-agent systems are presented, which balances the communication energy and control energy of the systems. Finally, the simulation results show that the topology optimization based on the controller optimization is able to improve the system performance.