{"title":"Mamdani FLC与各种含义","authors":"I. Iancu, M. Colhon","doi":"10.1109/SYNASC.2009.32","DOIUrl":null,"url":null,"abstract":"The task of the standard Mamdani fuzzy logic controller is to find a crisp control action from the fuzzy rule-base and from a set of crisp inputs. Because the interval inputs are frequently used in various domains (online shopping, for instance), in this paper we propose an extension of this type of controller which works with intervals as inputs and with various implication operators. For any implication we obtain a crisp value as output. Finally, these outputs are combined to obtain the overall crisp output action of the system.","PeriodicalId":286180,"journal":{"name":"2009 11th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Mamdani FLC with Various Implications\",\"authors\":\"I. Iancu, M. Colhon\",\"doi\":\"10.1109/SYNASC.2009.32\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The task of the standard Mamdani fuzzy logic controller is to find a crisp control action from the fuzzy rule-base and from a set of crisp inputs. Because the interval inputs are frequently used in various domains (online shopping, for instance), in this paper we propose an extension of this type of controller which works with intervals as inputs and with various implication operators. For any implication we obtain a crisp value as output. Finally, these outputs are combined to obtain the overall crisp output action of the system.\",\"PeriodicalId\":286180,\"journal\":{\"name\":\"2009 11th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing\",\"volume\":\"40 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-09-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 11th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SYNASC.2009.32\",\"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 11th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SYNASC.2009.32","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The task of the standard Mamdani fuzzy logic controller is to find a crisp control action from the fuzzy rule-base and from a set of crisp inputs. Because the interval inputs are frequently used in various domains (online shopping, for instance), in this paper we propose an extension of this type of controller which works with intervals as inputs and with various implication operators. For any implication we obtain a crisp value as output. Finally, these outputs are combined to obtain the overall crisp output action of the system.