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Probability-dependent filtering for nonlinear stochastic systems with missing measurements and randomly occurring communication delays

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  • Yan Che
  • Huisheng Shu
  • Hua Yang
  • Derui Ding

Abstract

In this article, the H∞ filtering problem is investigated for a class of nonlinear stochastic systems with incomplete measurements. The considered incomplete measurements include both the missing measurements and the randomly occurring communication delays. By using a set of Kronecker delta functions, a unified measurement model is employed to describe the phenomena of random communication delays and missing measurements. The purpose of the problem addressed is to design an H∞ filter such that, for all nonlinearities, incomplete measurements and external disturbances, the filtering error dynamics is exponentially mean-square stable and the H∞-norm requirement is satisfied. A sufficient condition for the existence of the desired filter is established in terms of certain linear matrix inequalities. A numerical example is given to illustrate the effectiveness of the proposed filter scheme.

Suggested Citation

  • Yan Che & Huisheng Shu & Hua Yang & Derui Ding, 2013. "Probability-dependent filtering for nonlinear stochastic systems with missing measurements and randomly occurring communication delays," International Journal of Systems Science, Taylor & Francis Journals, vol. 44(7), pages 1264-1273.
    • Handle: RePEc:taf:tsysxx:v:44:y:2013:i:7:p:1264-1273
    DOI: 10.1080/00207721.2012.659712
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    Cited by:

    1. M.V. Basin & M. Hernandez-Gonzalez, 2016. "Discrete-time filtering for nonlinear polynomial systems," International Journal of Systems Science, Taylor & Francis Journals, vol. 47(9), pages 2058-2066, July.

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