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    Delay-dependent robust fault detection for Markovian jump systems with partly unknown transition rates

    Access Status
    Fulltext not available
    Authors
    Chen, F.
    Yin, YanYan
    Liu, F.
    Date
    2016
    Type
    Journal Article
    
    Metadata
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    Citation
    Chen, F. and Yin, Y. and Liu, F. 2016. Delay-dependent robust fault detection for Markovian jump systems with partly unknown transition rates. Journal of the Franklin Institute. 353 (2): pp. 426-447.
    Source Title
    Journal of the Franklin Institute
    DOI
    10.1016/j.jfranklin.2015.12.001
    ISSN
    0016-0032
    School
    School of Electrical Engineering, Computing and Mathematical Science (EECMS)
    URI
    http://hdl.handle.net/20.500.11937/61111
    Collection
    • Curtin Research Publications
    Abstract

    This paper focuses on delay-dependent robust fault detection (RFD) problem for continuous-time Markovian jump systems (MJSs) with partly unknown transition rates and time-varying delay. Free-connection weighting matrices are firstly addressed to robust fault detection filter design, which reduce the conservatism caused by fixed-connection weighting matrices. By considering Lyapunov stability theory, new delay-dependent stochastic stability criteria are eatablished in terms of linear matrix inequalities (LMIs). Based on this, sufficient conditions are given and proved to guarantee the existence of the robust fault detection filter system. Furthermore, an optimization design approach is derived with an improved cone complementarity linearization algorithm. Finally, a simulation example is given to show that the designed robust fault detection filter can detect the faults sensitively, and also respond robustly to unknown disturbances.

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