{"title":"不确定系统的非线性参数模糊控制","authors":"Yih-Guang Leu, Chun-Yao Chen, Chin-Ming Hong","doi":"10.1109/FUZZY.2009.5277075","DOIUrl":null,"url":null,"abstract":"In this paper, a nonlinear parameter fuzzy control scheme is proposed for a class of uncertain systems without all states measurement. In the control scheme, a fuzzy identifier without prior knowledge on membership functions is merged into direct adaptive control by means of a linear state estimator. Since the structure of the fuzzy identifier is nonlinear in the adjusted parameters, the fuzzy identifier uses a mean method to develop adaptive laws. Finally, an example is provided to demonstrate the effectiveness of the proposed control scheme.","PeriodicalId":117895,"journal":{"name":"2009 IEEE International Conference on Fuzzy Systems","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2009-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Nonlinear parameter fuzzy control for uncertain systemswith only system output measurement\",\"authors\":\"Yih-Guang Leu, Chun-Yao Chen, Chin-Ming Hong\",\"doi\":\"10.1109/FUZZY.2009.5277075\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a nonlinear parameter fuzzy control scheme is proposed for a class of uncertain systems without all states measurement. In the control scheme, a fuzzy identifier without prior knowledge on membership functions is merged into direct adaptive control by means of a linear state estimator. Since the structure of the fuzzy identifier is nonlinear in the adjusted parameters, the fuzzy identifier uses a mean method to develop adaptive laws. Finally, an example is provided to demonstrate the effectiveness of the proposed control scheme.\",\"PeriodicalId\":117895,\"journal\":{\"name\":\"2009 IEEE International Conference on Fuzzy Systems\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-10-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 IEEE International Conference on Fuzzy Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FUZZY.2009.5277075\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE International Conference on Fuzzy Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FUZZY.2009.5277075","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Nonlinear parameter fuzzy control for uncertain systemswith only system output measurement
In this paper, a nonlinear parameter fuzzy control scheme is proposed for a class of uncertain systems without all states measurement. In the control scheme, a fuzzy identifier without prior knowledge on membership functions is merged into direct adaptive control by means of a linear state estimator. Since the structure of the fuzzy identifier is nonlinear in the adjusted parameters, the fuzzy identifier uses a mean method to develop adaptive laws. Finally, an example is provided to demonstrate the effectiveness of the proposed control scheme.