LEADER 04391nam 22007095 450 001 9910254247903321 005 20220406235306.0 010 $a3-319-28847-4 024 7 $a10.1007/978-3-319-28847-5 035 $a(CKB)3710000000577065 035 $a(EBL)4354095 035 $a(SSID)ssj0001606890 035 $a(PQKBManifestationID)16317683 035 $a(PQKBTitleCode)TC0001606890 035 $a(PQKBWorkID)14895618 035 $a(PQKB)11613875 035 $a(DE-He213)978-3-319-28847-5 035 $a(MiAaPQ)EBC4354095 035 $a(PPN)191701955 035 $a(EXLCZ)993710000000577065 100 $a20160119d2016 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aAnalysis and design of Markov jump systems with complex transition probabilities$b[electronic resource] /$fby Lixian Zhang, Ting Yang, Peng Shi, Yanzheng Zhu 205 $a1st ed. 2016. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2016. 215 $a1 online resource (268 p.) 225 1 $aStudies in Systems, Decision and Control,$x2198-4182 ;$v54 300 $aDescription based upon print version of record. 311 $a3-319-28846-6 320 $aIncludes bibliographical references and index. 327 $aIntroduction -- Part I Partially Unknown TPs -- Part II Piecewise Homogeneous TPs.-Part III Memory TPs. 330 $aThe book addresses the control issues such as stability analysis, control synthesis and filter design of Markov jump systems with the above three types of TPs, and thus is mainly divided into three parts. Part I studies the Markov jump systems with partially unknown TPs. Different methodologies with different conservatism for the basic stability and stabilization problems are developed and compared. Then the problems of state estimation, the control of systems with time-varying delays, the case involved with both partially unknown TPs and uncertain TPs in a composite way are also tackled. Part II deals with the Markov jump systems with piecewise homogeneous TPs. Methodologies that can effectively handle control problems in the scenario are developed, including the one coping with the asynchronous switching phenomenon between the currently activated system mode and the controller/filter to be designed. Part III focuses on the Markov jump systems with memory TPs. The concept of ?-mean square stability is proposed such that the stability problem can be solved via a finite number of conditions. The systems involved with nonlinear dynamics (described via the Takagi-Sugeno fuzzy model) are also investigated. Numerical and practical examples are given to verify the effectiveness of the obtained theoretical results. Finally, some perspectives and future works are presented to conclude the book. 410 0$aStudies in Systems, Decision and Control,$x2198-4182 ;$v54 606 $aControl engineering 606 $aComputational complexity 606 $aSystem theory 606 $aStatistical physics 606 $aControl and Systems Theory$3https://scigraph.springernature.com/ontologies/product-market-codes/T19010 606 $aComplexity$3https://scigraph.springernature.com/ontologies/product-market-codes/T11022 606 $aSystems Theory, Control$3https://scigraph.springernature.com/ontologies/product-market-codes/M13070 606 $aApplications of Nonlinear Dynamics and Chaos Theory$3https://scigraph.springernature.com/ontologies/product-market-codes/P33020 615 0$aControl engineering. 615 0$aComputational complexity. 615 0$aSystem theory. 615 0$aStatistical physics. 615 14$aControl and Systems Theory. 615 24$aComplexity. 615 24$aSystems Theory, Control. 615 24$aApplications of Nonlinear Dynamics and Chaos Theory. 676 $a620 700 $aZhang$b Lixian$4aut$4http://id.loc.gov/vocabulary/relators/aut$01060647 702 $aYang$b Ting$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aShi$b Peng$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aZhu$b Yanzheng$4aut$4http://id.loc.gov/vocabulary/relators/aut 906 $aBOOK 912 $a9910254247903321 996 $aAnalysis and Design of Markov Jump Systems with Complex Transition Probabilities$92514742 997 $aUNINA