{"title":"H∞ and QFT robust control designs for level control plant","authors":"Y. Kouhi, B. Labibi, Alireza Fatehi, R. Adlgostar","doi":"10.1109/INDCON.2008.4768755","DOIUrl":null,"url":null,"abstract":"In this paper two robust controllers are designed for a practical process trainer level plant. The system nonlinearity, time delay and change of parameters are the main problems in design of a desired controller for this plant. To design a controller, the linear models of the system and the disturbance models at different operating points are derived. Then, a parametric uncertainty profile is obtained by system identification strategies which is used in QFT control design. Indeed, for Hinfin control design a multiplicative unstructured model is extracted from the parametric uncertainty. All constraints in control design, disturbance rejection and control signal are derived. Based on these constraints, appropriate controllers are determined. To improve robust performance mu-synthesis with DK iteration is used. Finally all results are compared by applying the different controllers to the plant.","PeriodicalId":196254,"journal":{"name":"2008 Annual IEEE India Conference","volume":"57 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 Annual IEEE India Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INDCON.2008.4768755","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
In this paper two robust controllers are designed for a practical process trainer level plant. The system nonlinearity, time delay and change of parameters are the main problems in design of a desired controller for this plant. To design a controller, the linear models of the system and the disturbance models at different operating points are derived. Then, a parametric uncertainty profile is obtained by system identification strategies which is used in QFT control design. Indeed, for Hinfin control design a multiplicative unstructured model is extracted from the parametric uncertainty. All constraints in control design, disturbance rejection and control signal are derived. Based on these constraints, appropriate controllers are determined. To improve robust performance mu-synthesis with DK iteration is used. Finally all results are compared by applying the different controllers to the plant.