{"title":"离散时滞正系统鲁棒模型预测控制","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":"{\"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}","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}
Robust model predictive control of discrete-time delayed positive systems
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.