Titlebook: Analysis and Design of Singular Markovian Jump Systems; Guoliang Wang,Qingling Zhang,Xinggang Yan Book 2015 Springer International Publish

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Stability, as well as stochastic admissibility, is established by choosing an .-dependent Lyapunov function and only depends on stability bound. It is worth mentioning that the stability results proposed in this chapter will play important roles in dealing with other problems discussed in this book.

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, Control,is developed in the LMI setting, where the TRM can be uncertain, partially unknown and designed, and both . MIC and MDCs are obtained simultaneously. Based on these methods, improved results in terms of considering the probabilities of MIC and MDCs taking place are presented. The available probabili

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Stabilization,table and has desired performances. Due to singular Markovian jump systems containing singular derivative matrix and Markov property simultaneously, the control synthesis of stabilization of the SMJSs becomes complex especially when the underlying SMJSs have some general conditions. In this chapter,

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Filtering,s of a given system through noisy measurement. Particularly, . filtering has become a hot topic due to the powerful signal estimation and good robustness performance. In this chapter, the problem of . filtering for SMJSs will be considered. When there are uncertainties in TRM, conditions for robust