{"title":"时空动态系统的输出反馈后退水平控制","authors":"T. Hashimoto, Y. Takiguchi, T. Ohtsuka","doi":"10.1109/ASCC.2013.6606019","DOIUrl":null,"url":null,"abstract":"Receding horizon control problem is investigated here for a generalized class of spatiotemporal dynamic systems. Receding horizon controllers often assume that all state variables are exactly known. However, it is usual that the state variables of systems are measured through outputs, hence, only limited parts of them can be used directly. Moreover, the output signals may be disturbed by process and sensor noises. In this study, we develop a design method of output feedback receding horizon control for a generalized class of spatiotemporal dynamic systems. We apply the contraction mapping method and unscented Kalman filter for solving the optimization and estimation problems, respectively. The effectiveness of the proposed method is verified by numerical simulations.","PeriodicalId":6304,"journal":{"name":"2013 9th Asian Control Conference (ASCC)","volume":"1923 1","pages":"1-6"},"PeriodicalIF":0.0000,"publicationDate":"2013-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Output Feedback receding horizon control for spatiotemporal dynamic systems\",\"authors\":\"T. Hashimoto, Y. Takiguchi, T. Ohtsuka\",\"doi\":\"10.1109/ASCC.2013.6606019\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Receding horizon control problem is investigated here for a generalized class of spatiotemporal dynamic systems. Receding horizon controllers often assume that all state variables are exactly known. However, it is usual that the state variables of systems are measured through outputs, hence, only limited parts of them can be used directly. Moreover, the output signals may be disturbed by process and sensor noises. In this study, we develop a design method of output feedback receding horizon control for a generalized class of spatiotemporal dynamic systems. We apply the contraction mapping method and unscented Kalman filter for solving the optimization and estimation problems, respectively. The effectiveness of the proposed method is verified by numerical simulations.\",\"PeriodicalId\":6304,\"journal\":{\"name\":\"2013 9th Asian Control Conference (ASCC)\",\"volume\":\"1923 1\",\"pages\":\"1-6\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-06-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 9th Asian Control Conference (ASCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ASCC.2013.6606019\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 9th Asian Control Conference (ASCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASCC.2013.6606019","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Output Feedback receding horizon control for spatiotemporal dynamic systems
Receding horizon control problem is investigated here for a generalized class of spatiotemporal dynamic systems. Receding horizon controllers often assume that all state variables are exactly known. However, it is usual that the state variables of systems are measured through outputs, hence, only limited parts of them can be used directly. Moreover, the output signals may be disturbed by process and sensor noises. In this study, we develop a design method of output feedback receding horizon control for a generalized class of spatiotemporal dynamic systems. We apply the contraction mapping method and unscented Kalman filter for solving the optimization and estimation problems, respectively. The effectiveness of the proposed method is verified by numerical simulations.