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    Gain-scheduled fault detection on stochastic nonlinear systems with partially known transition jump rates

    Access Status
    Fulltext not available
    Authors
    Yin, YanYan
    Shi, P.
    Liu, F.
    Pan, J.
    Date
    2012
    Type
    Journal Article
    
    Metadata
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    Citation
    Yin, Y. and Shi, P. and Liu, F. and Pan, J. 2012. Gain-scheduled fault detection on stochastic nonlinear systems with partially known transition jump rates. Nonlinear Analysis: Real World Applications. 13 (1): pp. 359-369.
    Source Title
    Nonlinear Analysis: Real World Applications
    DOI
    10.1016/j.nonrwa.2011.07.043
    ISSN
    1468-1218
    School
    Department of Mathematics and Statistics
    URI
    http://hdl.handle.net/20.500.11937/52409
    Collection
    • Curtin Research Publications
    Abstract

    In this paper, the problem of continuous gain-scheduled fault detection (FD) is studied for a class of stochastic nonlinear systems which possesses partially known jump rates. Initially, by using gradient linearization approach, the nonlinear stochastic system is described by a series of linear jump models at some selected working points. Subsequently, observer-based residual generator is constructed for each jump linear system. Then, a new observer-design method is proposed for each re-constructed system to design H8 observers that minimize the influences of the disturbances, and to formulate a new performance index that increase the sensitivity to faults. Finally, continuous gain-scheduled approach is employed to design continuous FD observers on the whole nonlinear stochastic system. Simulation example is given to show the effectiveness and potential of the developed techniques. © 2011 Elsevier Ltd. All rights reserved.

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