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The joint optimal filtering and fault detection for multi-rate sensor fusion under unknown inputs

机译：未知输入下多速率传感器融合的联合最优滤波和故障检测

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In multi-sensor fusion, it is hard to guarantee that all sensors have an identical sampling rate, especially in the distributive and/or heterogeneous case. Meanwhile, stochastic noise, unknown inputs (Us), and faults may coexist in complex environment. To this end, we propose the problem of joint optimal filtering and fault detection (FD) for multi-rate sensor fusion subject to UIs, stochastic noise with known covariance, and faults imposed on the actuator and sensors. Furthermore, the new scheme of optimal multi-rate observer (MRO) is presented and applied to detect faults. The observer parameters are determined optimally in pursuit of the UI decoupling and maximizing noise attenuation under the causality constraint due to multi-rate nature. Finally, the output estimation error of the MRO is used as a residual signal for FD via a hypothesis test in which the threshold is adaptively designed according to the MRO parameters. One numerical example is given to show the effectiveness of our proposed method. (C) 2015 Elsevier B.V. All rights reserved.
机译：在多传感器融合中，尤其是在分布式和/或异构情况下，很难保证所有传感器都具有相同的采样率。同时，随机噪声，未知输入（Us）和故障可能在复杂的环境中共存。为此，我们提出了针对多速率传感器融合的联合最优滤波和故障检测（FD）问题，这些融合受UI，具有已知协方差的随机噪声以及施加在执行器和传感器上的故障的影响。此外，提出了一种新的最优多速率观测器（MRO）方案，并将其应用于故障检测。观察者参数是最佳确定的，以追求UI解耦并在多因数性质的因果约束下最大化噪声衰减。最后，通过假设检验将MRO的输出估计误差用作FD的残差信号，在该假设检验中，根据MRO参数自适应地设计了阈值。数值例子表明了该方法的有效性。 （C）2015 Elsevier B.V.保留所有权利。

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