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    Robust Filtering for Nonlinear Nonhomogeneous Markov Jump Systems by Fuzzy Approximation Approach

    228585.pdf (349.3Kb)
    Access Status
    Open access
    Authors
    Yin, Y.
    Shi, Peng
    Liu, F.
    Teo, Kok Lay
    Lim, C.
    Date
    2015
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Yin, Y. and Shi, P. and Liu, F. and Teo, K.L. and Lim, C. 2015. Robust Filtering for Nonlinear Nonhomogeneous Markov Jump Systems by Fuzzy Approximation Approach. IEEE Transactions on Cybernetics. 45 (9): pp. 1706-1716.
    Source Title
    IEEE Transactions on Cybernetics
    DOI
    10.1109/TCYB.2014.2358680
    ISSN
    2168-2267
    Remarks

    © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

    URI
    http://hdl.handle.net/20.500.11937/42887
    Collection
    • Curtin Research Publications
    Abstract

    This paper addresses the problem of robust fuzzy L2 - L∞ filtering for a class of uncertain nonlinear discretetime Markov jump systems (MJSs) with nonhomogeneous jump processes. The Takagi–Sugeno fuzzy model is employed to represent such nonlinear nonhomogeneous MJS with norm-bounded parameter uncertainties. In order to decrease conservation, a polytope Lyapunov function which evolves as a convex function is employed, and then, under the designed mode-dependent and variation-dependent fuzzy filter which includes the membership functions, a sufficient condition is presented to ensure that the filtering error dynamic system is stochastically stable and that it has a prescribed L2 - L∞ performance index. Two simulated examples are given to demonstrate the effectiveness and advantages of the proposed techniques.

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