Filter design for discrete-time Markovian jump singular systems with its application to fault detection

Xiuming Yao, Yaowen Feng, Ligang Wu, Wei Xing Zheng

    Research output: Chapter in Book / Conference PaperConference Paper

    3 Citations (Scopus)

    Abstract

    This paper is concerned with the problem of fault detection for discrete-time Markovian jump singular systems with intermittent measurements. The measurements transmission from the plant to the fault detection filter is assumed to be imperfect and a stochastic variable is utilized to model the phenomenon of data missing. Our attention is focused on the design of a fault detection filter such that the residual system is stochastic Markovian jump admissible and satisfies some scheduled performance. A new necessary and sufficient condition for a class of discrete-time Markovian jump singular systems to be stochastic Markovian jump admissible is proposed in the form of strict linear matrix inequalities (LMIs). Sufficient conditions are proposed for the existence of fault detection filter. Finally, a numerical example is provided to illustrate the usefulness and applicability of the developed theoretical results.
    Original languageEnglish
    Title of host publicationProceedings of the 3rd International Symposium on Systems and Control in Aeronautics and Astronautics (ISSCAA 2010), Harbin China (8-10 Jun. 2010)
    PublisherIEEE Press
    Pages321-326
    Number of pages6
    ISBN (Print)9781424475056
    Publication statusPublished - 2010
    EventInternational Symposium on Systems and Control in Aeronautics and Astronautics -
    Duration: 1 Jan 2010 → …

    Conference

    ConferenceInternational Symposium on Systems and Control in Aeronautics and Astronautics
    Period1/01/10 → …

    Keywords

    • Markov processes
    • neural networks (computer science)

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