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Robust Filtering for State and Fault Estimation of Linear Stochastic Systems with Unknown Disturbance

机译：未知干扰线性随机系统状态和故障估计的鲁棒滤波

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摘要

This paper presents a new robust filter structure to solve the simultaneous state and fault estimation problem of linear stochastic discrete-time systems with unknown disturbance. The method is based on the assumption that the fault and the unknown disturbance affect both the system state and the output, and no prior knowledge about their dynamical evolution is available. By making use of an optimal three-stage Kalman filtering method, an augmented fault and unknown disturbance models, an augmented robust three-stage Kalman filter (ARThSKF) is developed. The unbiasedness conditions and minimum-variance property of the proposed filter are provided. An illustrative example is given to apply this filter and to compare it with the existing literature results.
机译：本文提出了一种新的鲁棒滤波器结构，以解决具有未知扰动的线性随机离散时间系统的同时状态和故障估计问题。该方法基于以下假设：故障和未知干扰会影响系统状态和输出，并且没有关于其动态演化的先验知识。通过使用最佳的三级卡尔曼滤波方法，增强的故障和未知干扰模型，开发了增强的鲁棒三级卡尔曼滤波器（ARThSKF）。提供了所提出的滤波器的无偏条件和最小方差性质。给出了一个说明性示例，可以应用该过滤器并将其与现有文献结果进行比较。

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  • 来源
    《Mathematical Problems in Engineering》 |2010年第3期|p.277-300|共24页
  • 作者

    Fayçal Ben Hmida; Karim Khémiri; José Ragot; Moncef Gossa;

  • 作者单位

    Electrical Engineering Department of ESSTT, Research Unit C3S, Tunis University,5 Avenue Taha Hussein, BP 56,1008 Tunis, Tunisia;

    Electrical Engineering Department of ESSTT, Research Unit C3S, Tunis University,5 Avenue Taha Hussein, BP 56,1008 Tunis, Tunisia;

    Electrical Engineering Department, Research Laboratory CRAN (CNRS UMR 7039), Nancy University,2 Avenue de laforêt de Haye, 54516 Vandoeuvre-les-Nancy Cedex, France;

    Electrical Engineering Department of ESSTT, Research Unit C3S, Tunis University,5 Avenue Taha Hussein, BP 56,1008 Tunis, Tunisia;

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