M. Turki, Ismail Oukkacha, N. Langlois, A. Yassine, M. Camara, B. Dakyo
{"title":"A New Tuning Approach for MPC Applied to a Disturbed DC Motor","authors":"M. Turki, Ismail Oukkacha, N. Langlois, A. Yassine, M. Camara, B. Dakyo","doi":"10.1109/CoDIT.2018.8394814","DOIUrl":null,"url":null,"abstract":"In order to get correct results using the Model Predictive Control (MPC), one must find the suitable values of its parameters. Despite a large number of papers in literature on MPC tuning methods, there is no available analytical approach permitting to identify explicitly the robustness area of a process independently of its order. Here we intend to overcome this limit thanks to an analytical one. The interest of our approach is to be applicable to a wide set of linear controllable and observable single-input single-output (SISO) processes. The issues of optimal closed-loop stability and the energy consumed are addressed in this paper. The proposed method is tested experimentally via a DC motor. Finally, a performance comparison is made with existing methods to emphasize its effectiveness.","PeriodicalId":128011,"journal":{"name":"2018 5th International Conference on Control, Decision and Information Technologies (CoDIT)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 5th International Conference on Control, Decision and Information Technologies (CoDIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CoDIT.2018.8394814","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
In order to get correct results using the Model Predictive Control (MPC), one must find the suitable values of its parameters. Despite a large number of papers in literature on MPC tuning methods, there is no available analytical approach permitting to identify explicitly the robustness area of a process independently of its order. Here we intend to overcome this limit thanks to an analytical one. The interest of our approach is to be applicable to a wide set of linear controllable and observable single-input single-output (SISO) processes. The issues of optimal closed-loop stability and the energy consumed are addressed in this paper. The proposed method is tested experimentally via a DC motor. Finally, a performance comparison is made with existing methods to emphasize its effectiveness.