{"title":"基于模糊c均值聚类和模糊增益调度的二元精馏塔模糊监控控制器设计与实现","authors":"K. Somsung, S. Pratishthananda","doi":"10.1109/ICCIS.2006.252355","DOIUrl":null,"url":null,"abstract":"In this paper, fuzzy supervisory PI controllers are developed and implemented on a pilot plant binary distillation column. Fuzzy c-means clustering technique is used in selecting membership functions and fuzzy rules are determined using fuzzy gain scheduling technique. Thus, the need of heuristic method for designing fuzzy membership functions and rules from expert knowledge is omitted. Then, the fuzzy supervisors adapt the parameters of the PI controllers on line. The task of the controllers is to perform dual composition control of the top and bottom products when the disturbances enter the column in the form of changes in feed flow rate. The results show that the fuzzy supervisory PI controllers achieve much better performance than the fixed PI controllers","PeriodicalId":296028,"journal":{"name":"2006 IEEE Conference on Cybernetics and Intelligent Systems","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Design and Implementation of Fuzzy Supervisory Controllers Using Fuzzy c-Means Clustering Combined with Fuzzy Gain Scheduling for a Binary Distillation Column\",\"authors\":\"K. Somsung, S. Pratishthananda\",\"doi\":\"10.1109/ICCIS.2006.252355\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, fuzzy supervisory PI controllers are developed and implemented on a pilot plant binary distillation column. Fuzzy c-means clustering technique is used in selecting membership functions and fuzzy rules are determined using fuzzy gain scheduling technique. Thus, the need of heuristic method for designing fuzzy membership functions and rules from expert knowledge is omitted. Then, the fuzzy supervisors adapt the parameters of the PI controllers on line. The task of the controllers is to perform dual composition control of the top and bottom products when the disturbances enter the column in the form of changes in feed flow rate. The results show that the fuzzy supervisory PI controllers achieve much better performance than the fixed PI controllers\",\"PeriodicalId\":296028,\"journal\":{\"name\":\"2006 IEEE Conference on Cybernetics and Intelligent Systems\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-06-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 IEEE Conference on Cybernetics and Intelligent Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCIS.2006.252355\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 IEEE Conference on Cybernetics and Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCIS.2006.252355","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Design and Implementation of Fuzzy Supervisory Controllers Using Fuzzy c-Means Clustering Combined with Fuzzy Gain Scheduling for a Binary Distillation Column
In this paper, fuzzy supervisory PI controllers are developed and implemented on a pilot plant binary distillation column. Fuzzy c-means clustering technique is used in selecting membership functions and fuzzy rules are determined using fuzzy gain scheduling technique. Thus, the need of heuristic method for designing fuzzy membership functions and rules from expert knowledge is omitted. Then, the fuzzy supervisors adapt the parameters of the PI controllers on line. The task of the controllers is to perform dual composition control of the top and bottom products when the disturbances enter the column in the form of changes in feed flow rate. The results show that the fuzzy supervisory PI controllers achieve much better performance than the fixed PI controllers
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