{"title":"T-S模糊时滞系统的鲁棒输出反馈控制","authors":"Chian-Song Chiu, W. Yang, Tung-Sheng Chiang","doi":"10.1109/CICA.2013.6611662","DOIUrl":null,"url":null,"abstract":"This paper proposes output feedback control for uncertain T-S fuzzy systems with state and input delays. First, a fuzzy observer-based dynamic control method is introduced for stabilizing uncertain time-delay fuzzy systems. Based on the dynamic control scheme, the input delay is decoupled with the system states, so that the stability condition becomes simpler. Then, the robust stability conditions are derived and converted to solving linear matrix inequality problems (LMIPs) by a novel Lyapunov function. In turn, the controller and observer gains are able to be separately designed even in the presence of modeling uncertainty, state delay, and input delay. In comparison with current literatures, the controlled states and state estimation errors are guaranteed to be asymptotically stable with more relaxed conditions on the time delays. Numerical simulation and comparison results demonstrate the expected performance.","PeriodicalId":424622,"journal":{"name":"2013 IEEE Symposium on Computational Intelligence in Control and Automation (CICA)","volume":"93 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Robust output feedback control of T-S fuzzy time-delay systems\",\"authors\":\"Chian-Song Chiu, W. Yang, Tung-Sheng Chiang\",\"doi\":\"10.1109/CICA.2013.6611662\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes output feedback control for uncertain T-S fuzzy systems with state and input delays. First, a fuzzy observer-based dynamic control method is introduced for stabilizing uncertain time-delay fuzzy systems. Based on the dynamic control scheme, the input delay is decoupled with the system states, so that the stability condition becomes simpler. Then, the robust stability conditions are derived and converted to solving linear matrix inequality problems (LMIPs) by a novel Lyapunov function. In turn, the controller and observer gains are able to be separately designed even in the presence of modeling uncertainty, state delay, and input delay. In comparison with current literatures, the controlled states and state estimation errors are guaranteed to be asymptotically stable with more relaxed conditions on the time delays. Numerical simulation and comparison results demonstrate the expected performance.\",\"PeriodicalId\":424622,\"journal\":{\"name\":\"2013 IEEE Symposium on Computational Intelligence in Control and Automation (CICA)\",\"volume\":\"93 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-04-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE Symposium on Computational Intelligence in Control and Automation (CICA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CICA.2013.6611662\",\"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 IEEE Symposium on Computational Intelligence in Control and Automation (CICA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CICA.2013.6611662","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Robust output feedback control of T-S fuzzy time-delay systems
This paper proposes output feedback control for uncertain T-S fuzzy systems with state and input delays. First, a fuzzy observer-based dynamic control method is introduced for stabilizing uncertain time-delay fuzzy systems. Based on the dynamic control scheme, the input delay is decoupled with the system states, so that the stability condition becomes simpler. Then, the robust stability conditions are derived and converted to solving linear matrix inequality problems (LMIPs) by a novel Lyapunov function. In turn, the controller and observer gains are able to be separately designed even in the presence of modeling uncertainty, state delay, and input delay. In comparison with current literatures, the controlled states and state estimation errors are guaranteed to be asymptotically stable with more relaxed conditions on the time delays. Numerical simulation and comparison results demonstrate the expected performance.