Mohammad Biglar Begian, William W. Melek, J. Mendel
{"title":"Parametric design of stable type-2 TSK fuzzy systems","authors":"Mohammad Biglar Begian, William W. Melek, J. Mendel","doi":"10.1109/NAFIPS.2008.4531279","DOIUrl":null,"url":null,"abstract":"This paper presents a novel inference mechanism to design stable interval type-2 Takagi-Sugeno-Kang (TSK) dynamic fuzzy systems. The proposed engine introduces a closed form fur inference which replaces the type-reduction process. This closed form for inference enables the application of analytical methods for systematic modeling and control of uncertain fuzzy systems. Moreover, stability conditions are derived for type-2 TSK dynamic systems utilizing the proposed inference engine. The effectiveness of this new approach is validated through numerical examples. The methodology proposed herein can be used to systematically design stable type-2 TSK systems.","PeriodicalId":430770,"journal":{"name":"NAFIPS 2008 - 2008 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"54","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"NAFIPS 2008 - 2008 Annual Meeting of the North American Fuzzy Information Processing Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NAFIPS.2008.4531279","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 54
Abstract
This paper presents a novel inference mechanism to design stable interval type-2 Takagi-Sugeno-Kang (TSK) dynamic fuzzy systems. The proposed engine introduces a closed form fur inference which replaces the type-reduction process. This closed form for inference enables the application of analytical methods for systematic modeling and control of uncertain fuzzy systems. Moreover, stability conditions are derived for type-2 TSK dynamic systems utilizing the proposed inference engine. The effectiveness of this new approach is validated through numerical examples. The methodology proposed herein can be used to systematically design stable type-2 TSK systems.