{"title":"Comparisons of MRAFCS with the Smith predictor method and a PID controller for a time delay plant","authors":"Toru Idoue, C.-C. Hsu, S. Yamada, H. Fujikawa","doi":"10.1109/IECON.1999.819391","DOIUrl":null,"url":null,"abstract":"This paper proposes a new control method for time delay plant. Some systems have an unavoidable time delay. It is difficult to solve a plant with a time delay which makes the current signal shift and the controlled system become unstable when the time delay varies. Therefore, the authors applied fuzzy reasoning to a model reference adaptive control system. But the fuzzy rule set needs to be tuned by a trial and error type method. In this paper, the fuzzy rule sets are constructed by multi-operator self-tuning genetic algorithms.","PeriodicalId":378710,"journal":{"name":"IECON'99. Conference Proceedings. 25th Annual Conference of the IEEE Industrial Electronics Society (Cat. No.99CH37029)","volume":"249 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1999-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IECON'99. Conference Proceedings. 25th Annual Conference of the IEEE Industrial Electronics Society (Cat. No.99CH37029)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IECON.1999.819391","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper proposes a new control method for time delay plant. Some systems have an unavoidable time delay. It is difficult to solve a plant with a time delay which makes the current signal shift and the controlled system become unstable when the time delay varies. Therefore, the authors applied fuzzy reasoning to a model reference adaptive control system. But the fuzzy rule set needs to be tuned by a trial and error type method. In this paper, the fuzzy rule sets are constructed by multi-operator self-tuning genetic algorithms.