{"title":"基于最优模糊pid控制器的带钢厚度控制","authors":"Ren Shirong, Li Yuan, Zhang Lei, Su YingGuang","doi":"10.1109/CINC.2010.5643733","DOIUrl":null,"url":null,"abstract":"This paper introduces optimal fuzzy-PID control strategy into automatic gauge control system of cold steel rolling for improving control performances. Simulation results from MATLAB show that the PID controller has a better precision than the fuzzy-PID controller for an ideal model, but optimal fuzzy-PID controller has more robustness than the PID controller when there is noise and unmodelled dynamic in the control system.","PeriodicalId":227004,"journal":{"name":"2010 Second International Conference on Computational Intelligence and Natural Computing","volume":"86 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Strip thickness control based on optimal fuzzy-PID controller\",\"authors\":\"Ren Shirong, Li Yuan, Zhang Lei, Su YingGuang\",\"doi\":\"10.1109/CINC.2010.5643733\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper introduces optimal fuzzy-PID control strategy into automatic gauge control system of cold steel rolling for improving control performances. Simulation results from MATLAB show that the PID controller has a better precision than the fuzzy-PID controller for an ideal model, but optimal fuzzy-PID controller has more robustness than the PID controller when there is noise and unmodelled dynamic in the control system.\",\"PeriodicalId\":227004,\"journal\":{\"name\":\"2010 Second International Conference on Computational Intelligence and Natural Computing\",\"volume\":\"86 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-11-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 Second International Conference on Computational Intelligence and Natural Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CINC.2010.5643733\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Second International Conference on Computational Intelligence and Natural Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CINC.2010.5643733","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Strip thickness control based on optimal fuzzy-PID controller
This paper introduces optimal fuzzy-PID control strategy into automatic gauge control system of cold steel rolling for improving control performances. Simulation results from MATLAB show that the PID controller has a better precision than the fuzzy-PID controller for an ideal model, but optimal fuzzy-PID controller has more robustness than the PID controller when there is noise and unmodelled dynamic in the control system.
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