{"title":"大型互联系统非线性局部模型的分散鲁棒模糊控制器","authors":"Long Teng, Youyi Wang, W. Cai, Hua Li","doi":"10.1109/ICCA.2017.8003135","DOIUrl":null,"url":null,"abstract":"In this paper, a kind of decentralized robust fuzzy controller which uses nonlinear local models is designed for the control of large-scale interconnected systems. The approach of T-S fuzzy model with nonlinear local models rather than with linear local model can bring some advantages. Especially for large-scale interconnected systems which often contain a lot of complex nonlinear interconnection functions, the number of fuzzy rules can be decreased as well as the computational burden can be reduced. Meanwhile, the parameter uncertainties within each subsystem and in the interconnection of subsystems are also considered to achieve robustness of the system's performance. In addition, guaranteed cost control (H2 control) is realized and the control synthesis conditions are given by solving a set of linear matrix inequalities (LMIs). Simulation result is given to illustrate the effectiveness of the proposed method.","PeriodicalId":379025,"journal":{"name":"2017 13th IEEE International Conference on Control & Automation (ICCA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Decentralized robust fuzzy controller with nonlinear local models for large-scale interconnected systems\",\"authors\":\"Long Teng, Youyi Wang, W. Cai, Hua Li\",\"doi\":\"10.1109/ICCA.2017.8003135\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a kind of decentralized robust fuzzy controller which uses nonlinear local models is designed for the control of large-scale interconnected systems. The approach of T-S fuzzy model with nonlinear local models rather than with linear local model can bring some advantages. Especially for large-scale interconnected systems which often contain a lot of complex nonlinear interconnection functions, the number of fuzzy rules can be decreased as well as the computational burden can be reduced. Meanwhile, the parameter uncertainties within each subsystem and in the interconnection of subsystems are also considered to achieve robustness of the system's performance. In addition, guaranteed cost control (H2 control) is realized and the control synthesis conditions are given by solving a set of linear matrix inequalities (LMIs). Simulation result is given to illustrate the effectiveness of the proposed method.\",\"PeriodicalId\":379025,\"journal\":{\"name\":\"2017 13th IEEE International Conference on Control & Automation (ICCA)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 13th IEEE International Conference on Control & Automation (ICCA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCA.2017.8003135\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 13th IEEE International Conference on Control & Automation (ICCA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCA.2017.8003135","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Decentralized robust fuzzy controller with nonlinear local models for large-scale interconnected systems
In this paper, a kind of decentralized robust fuzzy controller which uses nonlinear local models is designed for the control of large-scale interconnected systems. The approach of T-S fuzzy model with nonlinear local models rather than with linear local model can bring some advantages. Especially for large-scale interconnected systems which often contain a lot of complex nonlinear interconnection functions, the number of fuzzy rules can be decreased as well as the computational burden can be reduced. Meanwhile, the parameter uncertainties within each subsystem and in the interconnection of subsystems are also considered to achieve robustness of the system's performance. In addition, guaranteed cost control (H2 control) is realized and the control synthesis conditions are given by solving a set of linear matrix inequalities (LMIs). Simulation result is given to illustrate the effectiveness of the proposed method.