{"title":"T-S模糊观察者的不可测前提回避","authors":"H. Moodi, D. Bustan","doi":"10.1109/ICCIAUTOM.2017.8258668","DOIUrl":null,"url":null,"abstract":"This paper addresses the problem of unmeasured premise variable in T-S fuzzy observers. Normally when the premise variable is unmeasured, observer design becomes rather challenging and computational burden increases. Here a simple method is introduced to avoid unmeasured premise variables by using the nonlinear local models in the fuzzy rules. The proposed method guarantees asymptotic convergence of state estimation error by Lyapunov stability analysis and linear matrix inequality (LMI) formulation. A practical example of two wheeled vehicle, illustrates effectiveness of the proposed method.","PeriodicalId":197207,"journal":{"name":"2017 5th International Conference on Control, Instrumentation, and Automation (ICCIA)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Unmeasurable premise avoidance in T-S fuzzy observers\",\"authors\":\"H. Moodi, D. Bustan\",\"doi\":\"10.1109/ICCIAUTOM.2017.8258668\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper addresses the problem of unmeasured premise variable in T-S fuzzy observers. Normally when the premise variable is unmeasured, observer design becomes rather challenging and computational burden increases. Here a simple method is introduced to avoid unmeasured premise variables by using the nonlinear local models in the fuzzy rules. The proposed method guarantees asymptotic convergence of state estimation error by Lyapunov stability analysis and linear matrix inequality (LMI) formulation. A practical example of two wheeled vehicle, illustrates effectiveness of the proposed method.\",\"PeriodicalId\":197207,\"journal\":{\"name\":\"2017 5th International Conference on Control, Instrumentation, and Automation (ICCIA)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 5th International Conference on Control, Instrumentation, and Automation (ICCIA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCIAUTOM.2017.8258668\",\"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 5th International Conference on Control, Instrumentation, and Automation (ICCIA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCIAUTOM.2017.8258668","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Unmeasurable premise avoidance in T-S fuzzy observers
This paper addresses the problem of unmeasured premise variable in T-S fuzzy observers. Normally when the premise variable is unmeasured, observer design becomes rather challenging and computational burden increases. Here a simple method is introduced to avoid unmeasured premise variables by using the nonlinear local models in the fuzzy rules. The proposed method guarantees asymptotic convergence of state estimation error by Lyapunov stability analysis and linear matrix inequality (LMI) formulation. A practical example of two wheeled vehicle, illustrates effectiveness of the proposed method.