{"title":"不确定互联动力系统最优跟踪的分布式自适应控制","authors":"Atsede G. Gebremedhin, Y. Fujisaki","doi":"10.1080/18824889.2022.2143634","DOIUrl":null,"url":null,"abstract":"This paper presents a distributed model reference adaptive control scheme for optimal tracking of an interconnected dynamical system in the presence of system/interconnection uncertainties. A reference model selection which achieves an optimal tracking for the nominal system is introduced by using linear quadratic regulator theory. Then an adaptive control law is developed for the uncertain interconnected dynamical system, where it employs the specified reference model. It is shown that the control law achieves the desired behaviour such that the output of the system asymptotically tracks the output of the reference model in the presence of the uncertainties. An explicit error bound regarding optimal tracking is also established.","PeriodicalId":413922,"journal":{"name":"SICE journal of control, measurement, and system integration","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Distributed adaptive control for optimal tracking of uncertain interconnected dynamical systems\",\"authors\":\"Atsede G. Gebremedhin, Y. Fujisaki\",\"doi\":\"10.1080/18824889.2022.2143634\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a distributed model reference adaptive control scheme for optimal tracking of an interconnected dynamical system in the presence of system/interconnection uncertainties. A reference model selection which achieves an optimal tracking for the nominal system is introduced by using linear quadratic regulator theory. Then an adaptive control law is developed for the uncertain interconnected dynamical system, where it employs the specified reference model. It is shown that the control law achieves the desired behaviour such that the output of the system asymptotically tracks the output of the reference model in the presence of the uncertainties. An explicit error bound regarding optimal tracking is also established.\",\"PeriodicalId\":413922,\"journal\":{\"name\":\"SICE journal of control, measurement, and system integration\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-06-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"SICE journal of control, measurement, and system integration\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/18824889.2022.2143634\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"SICE journal of control, measurement, and system integration","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/18824889.2022.2143634","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Distributed adaptive control for optimal tracking of uncertain interconnected dynamical systems
This paper presents a distributed model reference adaptive control scheme for optimal tracking of an interconnected dynamical system in the presence of system/interconnection uncertainties. A reference model selection which achieves an optimal tracking for the nominal system is introduced by using linear quadratic regulator theory. Then an adaptive control law is developed for the uncertain interconnected dynamical system, where it employs the specified reference model. It is shown that the control law achieves the desired behaviour such that the output of the system asymptotically tracks the output of the reference model in the presence of the uncertainties. An explicit error bound regarding optimal tracking is also established.