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    Robust fault detection of nonlinear markovian jump systems with partly unknown transition probabilities

    Access Status
    Fulltext not available
    Authors
    Shi, J.
    Yin, YanYan
    Liu, F.
    Date
    2016
    Type
    Journal Article
    
    Metadata
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    Citation
    Shi, J. and Yin, Y. and Liu, F. 2016. Robust fault detection of nonlinear markovian jump systems with partly unknown transition probabilities. ICIC Express Letters. 10 (6): pp. 1443-1450.
    Source Title
    ICIC Express Letters
    ISSN
    1881-803X
    School
    Department of Mathematics and Statistics
    URI
    http://hdl.handle.net/20.500.11937/63111
    Collection
    • Curtin Research Publications
    Abstract

    © 2016 ISSN.A robust fault detection observer (RFDO) is designed to solve the robust fault detection problem of the nonlinear Markovian jump systems (NMJSs) with partly unknown transition probabilities. With the method of T-S fuzzy linearization, the original NMJSs are described as a set of local linear models. On this basis, free-connection weighting matrices are introduced to RFDO. A series of linear matrix inequalities which ensure the stochastic asymptotic stability of the system are obtained by using the constructed Lyapunov function. Furthermore, the design problem is formulated as a two-objective optimization algorithm. A simulation example is given to show that the designed RFDO can not only detect the fault sensitively, but have the robustness to unknown disturbances.

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