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Filtering for Discrete Fuzzy Stochastic Time-Delay Systems with Sensor Saturation

机译：传感器饱和的离散模糊随机时滞系统的滤波

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摘要

This paper addresses the (H)_∞ filtering problem for discrete fuzzy stochastic systems with time-varying delay and sensor saturation. Random noise depending on state and external disturbance is also taken into account. A decomposition approach is employed to solve the characteristic of sensor saturation. The scaled small gain (SSG) theorem is extended to the stochastic systems, which is employed to handle with the time-varying delay by transforming the original system into the form of an interconnected system consisting of two subsystems. By the proposed Lyapunov-Krasovskii function, the scaled small gains of the subsystems are analyzed, respectively. Sufficient conditions for the stochastic stability of the filtering error system with a prescribed (H)_∞ level are established such that the gains of the (H)_∞ filter can be obtained explicitly. Finally, simulation results are presented to demonstrate the effectiveness of the proposed approach.
机译：本文研究了具有时变时滞和传感器饱和的离散模糊随机系统的（H）_∞滤波问题。还考虑了取决于状态和外部干扰的随机噪声。采用分解方法来解决传感器饱和度的特性。缩放小增益（SSG）定理扩展到了随机系统，该系统通过将原始系统转换为由两个子系统组成的互连系统的形式来处理时变延迟。通过提出的Lyapunov-Krasovskii函数，分别分析了子系统的缩放小增益。建立具有规定的（H）_∞等级的滤波误差系统的随机稳定性的充分条件，以便可以明确获得（H）_∞滤波器的增益。最后，仿真结果表明了该方法的有效性。

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  • 来源
    《Mathematical Problems in Engineering》 |2013年第3期|146325.1-146325.10|共10页
  • 作者

    Jia You; Shen Yin; Hamid R. Karimi;

  • 作者单位

    Research Institute of Intelligent Control and Systems, Harbin Institute of Technology, Heilongjiang 150001, China;

    College of Information Science and Technology, Bohai University, Jinzhou, Liaoning 121013, China;

    Department of Engineering, Faculty of Engineering and Science, University of Agder, 4879 Grimstad, Norway;

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