{"title":"模糊系统的矩阵表示与实现","authors":"Z. Miao, Xiangyu Zhao","doi":"10.1109/CIMA.2005.1662336","DOIUrl":null,"url":null,"abstract":"Fuzzy logic is wildly used in many fields in the recent years. It is also the theoretic base of fuzzy control. A novel matrix representation and implementation method is prompted in this paper. The new method employs the concepts of state space which achieved great success in the modern control theory and uses matrix to represent fuzzy models including the fuzzification, inference mechanism, rule base and defuzzification. Some new combining operators for fuzzy logic inference are also defined in this paper. To show the correctness and efficiency of the new method, a nonlinear system is discussed employing the new methods","PeriodicalId":306045,"journal":{"name":"2005 ICSC Congress on Computational Intelligence Methods and Applications","volume":"100 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Matrix representation and implementation of fuzzy system\",\"authors\":\"Z. Miao, Xiangyu Zhao\",\"doi\":\"10.1109/CIMA.2005.1662336\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Fuzzy logic is wildly used in many fields in the recent years. It is also the theoretic base of fuzzy control. A novel matrix representation and implementation method is prompted in this paper. The new method employs the concepts of state space which achieved great success in the modern control theory and uses matrix to represent fuzzy models including the fuzzification, inference mechanism, rule base and defuzzification. Some new combining operators for fuzzy logic inference are also defined in this paper. To show the correctness and efficiency of the new method, a nonlinear system is discussed employing the new methods\",\"PeriodicalId\":306045,\"journal\":{\"name\":\"2005 ICSC Congress on Computational Intelligence Methods and Applications\",\"volume\":\"100 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-12-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2005 ICSC Congress on Computational Intelligence Methods and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIMA.2005.1662336\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2005 ICSC Congress on Computational Intelligence Methods and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIMA.2005.1662336","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Matrix representation and implementation of fuzzy system
Fuzzy logic is wildly used in many fields in the recent years. It is also the theoretic base of fuzzy control. A novel matrix representation and implementation method is prompted in this paper. The new method employs the concepts of state space which achieved great success in the modern control theory and uses matrix to represent fuzzy models including the fuzzification, inference mechanism, rule base and defuzzification. Some new combining operators for fuzzy logic inference are also defined in this paper. To show the correctness and efficiency of the new method, a nonlinear system is discussed employing the new methods