{"title":"Temperature control of multidimensional system using decoupled MPC controllers","authors":"Jozef Kurilla","doi":"10.1109/PC.2017.7976239","DOIUrl":null,"url":null,"abstract":"This paper presents the connection between predictive control and simplification of MIMO system. A model of a part of administrative building is used to observe mutual thermal interactions between individual offices. Multivariable sixth-order system is converted into six linear mutually individual systems of first-order by input-output linearization (decoupling). These SISO systems are controlled by predictive a controller focusing on the accuracy of the room temperature respecting office occupancy profile. Included constraints make from control task the problem of quadratic programming. The final control structure takes advantage of the low computational burden of simple predictive controller and network communication, which ensures the inclusion of constraints. The mutual effect of the output variables and time response of control action is compared in a simulation study.","PeriodicalId":377619,"journal":{"name":"2017 21st International Conference on Process Control (PC)","volume":"100 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 21st International Conference on Process Control (PC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PC.2017.7976239","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
This paper presents the connection between predictive control and simplification of MIMO system. A model of a part of administrative building is used to observe mutual thermal interactions between individual offices. Multivariable sixth-order system is converted into six linear mutually individual systems of first-order by input-output linearization (decoupling). These SISO systems are controlled by predictive a controller focusing on the accuracy of the room temperature respecting office occupancy profile. Included constraints make from control task the problem of quadratic programming. The final control structure takes advantage of the low computational burden of simple predictive controller and network communication, which ensures the inclusion of constraints. The mutual effect of the output variables and time response of control action is compared in a simulation study.