Long Cheng, Kai Huang, Gang Chen, Biao Hu, A. Knoll
{"title":"Mixed-Criticality Control System with Performance and Robustness Guarantees","authors":"Long Cheng, Kai Huang, Gang Chen, Biao Hu, A. Knoll","doi":"10.1109/Trustcom/BigDataSE/ICESS.2017.311","DOIUrl":null,"url":null,"abstract":"Nowadays, many embedded systems consist of a mix of control applications and soft real-time tasks. This paper studies how to ensure the worst-case quality of control for control applications under disturbances while providing maximal resource to soft real-time tasks. To solve this problem, we propose a mixed-criticality control system model in which the tasks can switch between two operating modes, LO and HI, according to controlled plant states. In HI mode, the worst-case qualities of control to plants are guaranteed, while in LO mode, system resources are balanced between two classes of tasks. We compare our approach with other two approaches in the literature. Case study results demonstrate the effectiveness of our system model.","PeriodicalId":170253,"journal":{"name":"2017 IEEE Trustcom/BigDataSE/ICESS","volume":"144 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE Trustcom/BigDataSE/ICESS","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/Trustcom/BigDataSE/ICESS.2017.311","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
Nowadays, many embedded systems consist of a mix of control applications and soft real-time tasks. This paper studies how to ensure the worst-case quality of control for control applications under disturbances while providing maximal resource to soft real-time tasks. To solve this problem, we propose a mixed-criticality control system model in which the tasks can switch between two operating modes, LO and HI, according to controlled plant states. In HI mode, the worst-case qualities of control to plants are guaranteed, while in LO mode, system resources are balanced between two classes of tasks. We compare our approach with other two approaches in the literature. Case study results demonstrate the effectiveness of our system model.