文章基本信息

标题：Partial Sampled-Data State Feedback Control of Markov Jump Linear Systems ⁎
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作者：Rafael F. Cunha ; Gabriela W. Gabriel ; José C. Geromel 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2018
卷号：51
期号：25
页码：222-227
DOI：10.1016/j.ifacol.2018.11.109
语种：English
出版社：Elsevier
摘要：AbstractThis paper aims at designing a partial sampled-data state feedback control law for Markov jump linear systems (MJLS). The interesting feature of the control structure is that only the state variable is sampled, while the stochastic parameter that defines the Markov mode of the system used for control purposes is free to change at any time between samples. The main goal is to provide sufficient convex conditions for the existence of a solution for this class of control design problems in the context ofH∞andH2performances, which are expressed through Differential Linear Matrix Inequalities (DLMI). The proposed method is implemented using LMIs facilities and provides a minimum guaranteed cost control in only one shot. An example is solved for illustration and comparison.
关键词：KeywordsSampled-data systemsNetworked control systemsLMIconvex optimizationMarkov process