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Robust Filtering for Uncertain Discrete-Time Fuzzy Stochastic Systems with Sensor Nonlinearities and Time-Varying Delay

Author

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  • Mingang Hua
  • Pei Cheng
  • Juntao Fei
  • Jianyong Zhang
  • Junfeng Chen

Abstract

The robust filtering problem for a class of uncertain discrete-time fuzzy stochastic systems with sensor nonlinearities and time-varying delay is investigated. The parameter uncertainties are assumed to be time varying norm bounded in both the state and measurement equations. By using the Lyapunov stability theory and some new relaxed techniques, sufficient conditions are proposed to guarantee the robustly stochastic stability with a prescribed performance level of the filtering error system for all admissible uncertainties, sensor nonlinearities, and time-varying delays. These conditions are dependent on the lower and upper bounds of the time-varying delays and are obtained in terms of a linear matrix inequality (LMI). Finally, two simulation examples are provided to illustrate the effectiveness of the proposed methods.

Suggested Citation

  • Mingang Hua & Pei Cheng & Juntao Fei & Jianyong Zhang & Junfeng Chen, 2012. "Robust Filtering for Uncertain Discrete-Time Fuzzy Stochastic Systems with Sensor Nonlinearities and Time-Varying Delay," Journal of Applied Mathematics, Hindawi, vol. 2012, pages 1-25, December.
    • Handle: RePEc:hin:jnljam:402480
    DOI: 10.1155/2012/402480
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