Tadanao Zanma, Daiki Hashimoto, Kenta Koiwa, Kang-Zhi Liu
{"title":"Estimation of network traffic status and switching control of networked control systems with data dropout","authors":"Tadanao Zanma, Daiki Hashimoto, Kenta Koiwa, Kang-Zhi Liu","doi":"10.1049/cps2.12024","DOIUrl":null,"url":null,"abstract":"<p>The recent development of the communication technology accelerates studies of real-time networked control systems using networks. The data dropout is essentially unavoidable, especially in wireless networks and it results from transmission errors and network traffic congestion. Multiple time-varying network traffic status given by discrete-time homogeneous Markov chains is assumed. The authors estimate the network traffic status characterised by the probability matrix of the Markov chain online from the data dropout history. According to the estimation of network traffic status, an appropriate controller is selected to improve the control performance. The effectiveness of the proposed method is verified through simulations and experiments.</p>","PeriodicalId":36881,"journal":{"name":"IET Cyber-Physical Systems: Theory and Applications","volume":null,"pages":null},"PeriodicalIF":1.7000,"publicationDate":"2021-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/cps2.12024","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IET Cyber-Physical Systems: Theory and Applications","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1049/cps2.12024","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 1
Abstract
The recent development of the communication technology accelerates studies of real-time networked control systems using networks. The data dropout is essentially unavoidable, especially in wireless networks and it results from transmission errors and network traffic congestion. Multiple time-varying network traffic status given by discrete-time homogeneous Markov chains is assumed. The authors estimate the network traffic status characterised by the probability matrix of the Markov chain online from the data dropout history. According to the estimation of network traffic status, an appropriate controller is selected to improve the control performance. The effectiveness of the proposed method is verified through simulations and experiments.