{"title":"不确定非线性系统的模糊建模","authors":"Amira Aydi, M. Djemel, M. Chtourou","doi":"10.1109/STA.2014.7086738","DOIUrl":null,"url":null,"abstract":"This paper deals with fuzzy modeling of nonlinear systems affected by bounded uncertainties. The proposed model is composed of two parts: a linear uncertain part and a nonlinear part. The linear uncertain part is obtained by system linearization around some operating points. Nonlinear part parameters are estimated through the use of the descent gradient method. Finally, two examples are treated to illustrate the effectiveness of the proposed modeling method.","PeriodicalId":125957,"journal":{"name":"2014 15th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"On the fuzzy modeling of uncertain nonlinear systems\",\"authors\":\"Amira Aydi, M. Djemel, M. Chtourou\",\"doi\":\"10.1109/STA.2014.7086738\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper deals with fuzzy modeling of nonlinear systems affected by bounded uncertainties. The proposed model is composed of two parts: a linear uncertain part and a nonlinear part. The linear uncertain part is obtained by system linearization around some operating points. Nonlinear part parameters are estimated through the use of the descent gradient method. Finally, two examples are treated to illustrate the effectiveness of the proposed modeling method.\",\"PeriodicalId\":125957,\"journal\":{\"name\":\"2014 15th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 15th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/STA.2014.7086738\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 15th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/STA.2014.7086738","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
On the fuzzy modeling of uncertain nonlinear systems
This paper deals with fuzzy modeling of nonlinear systems affected by bounded uncertainties. The proposed model is composed of two parts: a linear uncertain part and a nonlinear part. The linear uncertain part is obtained by system linearization around some operating points. Nonlinear part parameters are estimated through the use of the descent gradient method. Finally, two examples are treated to illustrate the effectiveness of the proposed modeling method.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
