000 03423nam a22005655i 4500
001 978-3-319-28847-5
003 DE-He213
005 20200421112046.0
007 cr nn 008mamaa
008 160119s2016 gw | s |||| 0|eng d
020 _a9783319288475
_9978-3-319-28847-5
024 7 _a10.1007/978-3-319-28847-5
_2doi
050 4 _aTJ212-225
072 7 _aTJFM
_2bicssc
072 7 _aTEC004000
_2bisacsh
082 0 4 _a629.8
_223
100 1 _aZhang, Lixian.
_eauthor.
245 1 0 _aAnalysis and Design of Markov Jump Systems with Complex Transition Probabilities
_h[electronic resource] /
_cby Lixian Zhang, Ting Yang, Peng Shi, Yanzheng Zhu.
250 _a1st ed. 2016.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2016.
300 _aXVI, 263 p. 47 illus., 8 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aStudies in Systems, Decision and Control,
_x2198-4182 ;
_v54
505 0 _aIntroduction -- Part I Partially Unknown TPs -- Part II Piecewise Homogeneous TPs.-Part III Memory TPs.
520 _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 (Sv(B-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.
650 0 _aEngineering.
650 0 _aSystem theory.
650 0 _aStatistical physics.
650 0 _aComplexity, Computational.
650 0 _aControl engineering.
650 1 4 _aEngineering.
650 2 4 _aControl.
650 2 4 _aComplexity.
650 2 4 _aSystems Theory, Control.
650 2 4 _aNonlinear Dynamics.
700 1 _aYang, Ting.
_eauthor.
700 1 _aShi, Peng.
_eauthor.
700 1 _aZhu, Yanzheng.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319288468
830 0 _aStudies in Systems, Decision and Control,
_x2198-4182 ;
_v54
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-319-28847-5
912 _aZDB-2-ENG
942 _cEBK
999 _c56945
_d56945