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    Gain-scheduled robust fault detection on time-delay stochastic nonlinear systems

    Access Status
    Fulltext not available
    Authors
    Yin, YanYan
    Shi, P.
    Liu, F.
    Date
    2011
    Type
    Journal Article
    
    Metadata
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    Citation
    Yin, Y. and Shi, P. and Liu, F. 2011. Gain-scheduled robust fault detection on time-delay stochastic nonlinear systems. IEEE Transactions on Industrial Electronics. 58 (10): pp. 4908-4916.
    Source Title
    IEEE Transactions on Industrial Electronics
    DOI
    10.1109/TIE.2010.2103537
    ISSN
    0278-0046
    School
    Department of Mathematics and Statistics
    URI
    http://hdl.handle.net/20.500.11937/52127
    Collection
    • Curtin Research Publications
    Abstract

    This paper studies the problem of continuous gain-scheduled robust fault detection (RFD) on a class of time-delay stochastic nonlinear systems with partially known jump rates. By means of gradient linearization procedure, stochastic linear models and filter-based residual signal generators are constructed in the vicinity of selected operating states. Furthermore, in order to guarantee the sensitivity to faults and robustness against unknown inputs, an RFD filter (RFDF) is designed for such linear models by first designing H 8 filters that minimize the influences of the disturbances and modeling uncertainties and then a new performance index that increases the sensitivity to faults. Subsequently, a sufficient condition on the existence of RFDF is established in terms of linear matrix inequality techniques. Finally, a continuous gain-scheduled approach is employed to design continuous RFDFs on the entire nonlinear jump system. A simulation example is given to illustrate that the proposed RFDF can detect the faults correctly and shortly after the occurrences. © 2011 IEEE.

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