{"title":"二元精馏塔模糊规则控制器","authors":"Ashutosh Kumar Singh, B. Tyagi, Vishal Kumar","doi":"10.1145/2007052.2007086","DOIUrl":null,"url":null,"abstract":"In this paper a fuzzy logic based control scheme has been proposed for distillation column. Fuzzy Inference Systems (FIS) is proposed to adjust the manipulated variables to get the desired composition of products for a binary distillation column. To control the top and bottom product composition two separate fuzzy inference systems has been designed. The scheme uses fuzzy rules and reasoning to determine the desired outputs based on the error signal and its first difference","PeriodicalId":348804,"journal":{"name":"International Conference on Advances in Computing and Artificial Intelligence","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Fuzzy rule-based controller for binary distillation column\",\"authors\":\"Ashutosh Kumar Singh, B. Tyagi, Vishal Kumar\",\"doi\":\"10.1145/2007052.2007086\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper a fuzzy logic based control scheme has been proposed for distillation column. Fuzzy Inference Systems (FIS) is proposed to adjust the manipulated variables to get the desired composition of products for a binary distillation column. To control the top and bottom product composition two separate fuzzy inference systems has been designed. The scheme uses fuzzy rules and reasoning to determine the desired outputs based on the error signal and its first difference\",\"PeriodicalId\":348804,\"journal\":{\"name\":\"International Conference on Advances in Computing and Artificial Intelligence\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-07-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Advances in Computing and Artificial Intelligence\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2007052.2007086\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Advances in Computing and Artificial Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2007052.2007086","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fuzzy rule-based controller for binary distillation column
In this paper a fuzzy logic based control scheme has been proposed for distillation column. Fuzzy Inference Systems (FIS) is proposed to adjust the manipulated variables to get the desired composition of products for a binary distillation column. To control the top and bottom product composition two separate fuzzy inference systems has been designed. The scheme uses fuzzy rules and reasoning to determine the desired outputs based on the error signal and its first difference
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