{"title":"Stochastic stabilization of networked control systems with time-varying sampling periods","authors":"Yan Wang, Zeng-qi Sun","doi":"10.1109/ICCT.2008.4716112","DOIUrl":null,"url":null,"abstract":"This paper presents a stochastic control method for networked control systems (NCSs) with time-varying sampling periods and random delay. The random delay of the NCS is modelled as intervals governed by a Markov chain. With the switching of the sampling periods, a discrete-time Markovian jump system with parameter uncertainties is presented to model the NCS. By introducing a delay-compensating control term, we construct an augmented state feedback controller. The controller gains can be constructed via LMIs using the stochastic Lyapunov function approach. An example is given to show the proposed results.","PeriodicalId":259577,"journal":{"name":"2008 11th IEEE International Conference on Communication Technology","volume":"60 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 11th IEEE International Conference on Communication Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCT.2008.4716112","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
This paper presents a stochastic control method for networked control systems (NCSs) with time-varying sampling periods and random delay. The random delay of the NCS is modelled as intervals governed by a Markov chain. With the switching of the sampling periods, a discrete-time Markovian jump system with parameter uncertainties is presented to model the NCS. By introducing a delay-compensating control term, we construct an augmented state feedback controller. The controller gains can be constructed via LMIs using the stochastic Lyapunov function approach. An example is given to show the proposed results.