{"title":"Consensus control for linear systems in the presence of environmental and channel noise","authors":"S. Biswas, Q. Dong, Li Bai","doi":"10.1109/ISRCS.2011.6016103","DOIUrl":null,"url":null,"abstract":"This paper uses multi-agent concepts for the development of a decentralized control law for networked large scale systems in the presence of environmental noise and communication channel noise. The subsystems are assumed to be linear time invariant with Gaussian white noise appearing as an exogenous input. Each subsystem receives output information of other subsystems through the communication channel, which is then used to synthesize the control. The communication channel is also assumed to corrupt the signal with additive Gaussian White noise. Using the Lyapunov's approach, we develop a consensus protocol so that the various subsystems arrive at a weak consensus in the sense that the leader-follower state error remains within a small neighborhood of the origin. Simulation results are presented to illustrate the method.","PeriodicalId":336336,"journal":{"name":"2011 4th International Symposium on Resilient Control Systems","volume":"269-270 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 4th International Symposium on Resilient Control Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISRCS.2011.6016103","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
This paper uses multi-agent concepts for the development of a decentralized control law for networked large scale systems in the presence of environmental noise and communication channel noise. The subsystems are assumed to be linear time invariant with Gaussian white noise appearing as an exogenous input. Each subsystem receives output information of other subsystems through the communication channel, which is then used to synthesize the control. The communication channel is also assumed to corrupt the signal with additive Gaussian White noise. Using the Lyapunov's approach, we develop a consensus protocol so that the various subsystems arrive at a weak consensus in the sense that the leader-follower state error remains within a small neighborhood of the origin. Simulation results are presented to illustrate the method.