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Fault Diagnosis and Fault Tolerant Control Against Simultaneous Sensor and Actuator Faults for Linear Stochastic Systems

机译:线性随机系统对传感器和执行器同时故障的故障诊断和容错控制

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This paper presents the problem of robust fault diagnosis and accommodation for a class of linear stochastic systems where simultaneous actuator and sensor faults may occur at a given time. Firstly, based on Augmented Robust Three stage Kalman filters (ARThSKF) we obtained both the fault estimation and the residual signal. Then, residual evaluation is achieved by making use of an adaptive threshold adjustment algorithm based on the grey theory. Obtained results show that the false-alarm rates and the missing alarm rates are minimized by the developed method; also this approach detects small or incipient faults more effectively than the classical robust fault detection algorithms with fixed thresholds. Finally, an additive control input is introduced for cancelling out the fault's effect on the system. We evaluate our proposal through simulation and we demonstrate its feasibility.
机译:本文提出了一类线性随机系统的故障诊断和适应能力强的问题,在给定的时间可能同时发生执行器和传感器故障。首先,基于增强鲁棒三级卡尔曼滤波器(ARThSKF),我们获得了故障估计和残差信号。然后,通过使用基于灰色理论的自适应阈值调整算法来实现残差评估。所得结果表明,所开发的方法可以最大程度地降低误报率和漏报率。与采用固定阈值的经典鲁棒故障检测算法相比,该方法还可以更有效地检测小故障或初期故障。最后,引入了附加控制输入,以消除故障对系统的影响。我们通过仿真评估了我们的建议,并证明了其可行性。

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