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Unbiased Minimum-Variance Filter for State and Fault Estimation of Linear Time-Varying Systems with Unknown Disturbances

机译：带有未知扰动的线性时变系统的状态和故障估计的无偏最小方差滤波器

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摘要

This paper presents a new recursive filter to joint fault and state estimation of a linear time-varying discrete systems in the presence of unknown disturbances. The method is based on the assumption that no prior knowledge about the dynamical evolution of the fault and the disturbance is available. As the fault affects both the state and the output, but the disturbance affects only the state system. Initially, we study the particular case when the direct feedthrough matrix of the fault has full rank. In the second case, we propose an extension of the previous case by considering the direct feedthrough matrix of the fault with an arbitrary rank. The resulting filter is optimal in the sense of the unbiased minimum-variance (UMV) criteria. A numerical example is given in order to illustrate the proposed method.
机译：本文针对存在未知扰动的线性时变离散系统的联合故障和状态估计，提出了一种新的递归滤波器。该方法基于以下假设：没有关于故障和干扰的动态演化的现有知识。故障既影响状态又影响输出，但是干扰仅影响状态系统。最初，我们研究故障的直接馈通矩阵具有完整等级的特殊情况。在第二种情况下，我们建议通过考虑具有任意等级的故障的直接馈通矩阵来扩展前一种情况。在无偏最小方差（UMV）标准的意义上，所得的滤波器是最佳的。给出了一个数值例子来说明所提出的方法。

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  • 来源
    《Mathematical Problems in Engineering》 |2010年第1期|p.9.1-9.17|共17页
  • 作者

    Faycal Ben Hmida; Karim Khemiri; Jose Ragot; Moncef Gossa;

  • 作者单位

    Electrical Engineering Department, ESSTT-C3S, 5 Avenue Taha Hussein, BP 56,1008 Tunis, Tunisia;

    rnElectrical Engineering Department, ESSTT-C3S, 5 Avenue Taha Hussein, BP 56,1008 Tunis, Tunisia;

    rnElectrical Engineering Department, CRAN (CNRS UMR 7039), 2 Avenue de lafortt de Haye,54516 Vandceuvre-les-Nancy Cedex, France;

    rnElectrical Engineering Department, ESSTT-C3S, 5 Avenue Taha Hussein, BP 56,1008 Tunis, Tunisia;

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