{"title":"Improved H∞ filtering for continuous Markov jump linear systems","authors":"M. Shen, Guanghong Yang","doi":"10.1109/CCA.2009.5281135","DOIUrl":null,"url":null,"abstract":"This paper investigates the problem of H#x221E; filter design for a class of continuous Markov jump linear systems (MJLSs) with no-accessible jump mode. A new version of bound real lemma (BRL) which can guarantee the performance and the stochastically stability for MJLSs is proposed. Then, based on the BRL, a new approach for H∞ filtering is given. Compared with the existing design methods, more slack variables, which could lead to reduce conservativeness and give better H∞ performance, are introduced in the proposed approach. Furthermore, the whole design procedure can be accomplished by solving a set of linear matrix inequalities (LMIs). Finally, the effectiveness of the proposed H∞ filtering approach can be illustrated by numerical examples.","PeriodicalId":294950,"journal":{"name":"2009 IEEE Control Applications, (CCA) & Intelligent Control, (ISIC)","volume":"488 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE Control Applications, (CCA) & Intelligent Control, (ISIC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCA.2009.5281135","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 investigates the problem of H#x221E; filter design for a class of continuous Markov jump linear systems (MJLSs) with no-accessible jump mode. A new version of bound real lemma (BRL) which can guarantee the performance and the stochastically stability for MJLSs is proposed. Then, based on the BRL, a new approach for H∞ filtering is given. Compared with the existing design methods, more slack variables, which could lead to reduce conservativeness and give better H∞ performance, are introduced in the proposed approach. Furthermore, the whole design procedure can be accomplished by solving a set of linear matrix inequalities (LMIs). Finally, the effectiveness of the proposed H∞ filtering approach can be illustrated by numerical examples.