{"title":"Identification and control of a nonlinear bioreactor plant using classical and dynamical neural networks","authors":"M. Onder Efe, O. Kaynak","doi":"10.1109/ISIE.1997.648914","DOIUrl":null,"url":null,"abstract":"In this study, the identification and control of a bioreactor plant using neural networks is considered with three different control strategies, namely, inverse control strategy, self-learning control and dynamical neural units for control of nonlinear dynamical systems. The performance of these methods are compared using several comparison measures.","PeriodicalId":134474,"journal":{"name":"ISIE '97 Proceeding of the IEEE International Symposium on Industrial Electronics","volume":"171 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ISIE '97 Proceeding of the IEEE International Symposium on Industrial Electronics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISIE.1997.648914","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
In this study, the identification and control of a bioreactor plant using neural networks is considered with three different control strategies, namely, inverse control strategy, self-learning control and dynamical neural units for control of nonlinear dynamical systems. The performance of these methods are compared using several comparison measures.