{"title":"Robust model predictive control of discrete-time delayed positive systems","authors":"Hamed Mehrivash, M. Shafiei","doi":"10.1109/ICCIAUTOM.2017.8258669","DOIUrl":null,"url":null,"abstract":"This paper investigates a Robust Model Predictive Control (RMPC) for interval discrete-time linear positive systems with time-delays. A transformation is applied to the interval linear time-delay positive system to turn it into an interval linear positive system without delay. Then a single-step linear programming-based robust model predictive controller with dynamic feedback is employed to optimally stabilize the system. All the stability conditions are in a form that can be solved by linprog Toolbox in Matlab which is more effective than LMIs for positive systems. Meanwhile, in the proposed method computational burden (off-line and on-line) is very low. Finally an illustrative example is presented to show the effectiveness of the proposed method.","PeriodicalId":197207,"journal":{"name":"2017 5th International Conference on Control, Instrumentation, and Automation (ICCIA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 5th International Conference on Control, Instrumentation, and Automation (ICCIA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCIAUTOM.2017.8258669","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
This paper investigates a Robust Model Predictive Control (RMPC) for interval discrete-time linear positive systems with time-delays. A transformation is applied to the interval linear time-delay positive system to turn it into an interval linear positive system without delay. Then a single-step linear programming-based robust model predictive controller with dynamic feedback is employed to optimally stabilize the system. All the stability conditions are in a form that can be solved by linprog Toolbox in Matlab which is more effective than LMIs for positive systems. Meanwhile, in the proposed method computational burden (off-line and on-line) is very low. Finally an illustrative example is presented to show the effectiveness of the proposed method.