Robust Detection of Intermittent Faults of Linear Discrete-Time Stochastic Systems

Abstract

Abstract:

Abstract： In this paper, a robust detection method for intermittent faults (IFs) was proposed for a class of linear discrete-time stochastic systems, subject to unknown disturbances, process noises and measurement noises. A reduced-order unknown input observer was designed and a novel truncated residual was constructed by introducing a sliding time window, which is decoupled from the unknown disturbances, but sensitive to the IF. Two hypothesis tests were put forward to detect all the appearing time and the disappearing time of the IF, respectively. In addition, for the given false alarm rate and the missing detection rate, the detection thresholds for the appearing time and the disappearing time of the IF were rigorously designed for desired performances, respectively， and the detectability of the IF was also analyzed in a probabilistic sense. The simulation results on a satellite model were presented to verify the proposed method. The results illustrate that both the appearing time and the disappearing time of the IF can be detected fast and validly in spite of unknown disturbances.

Key words: intermittent fault (IF), robust detection, reduced-order unknown input observer, truncated residual signal

CLC Number:

TP 273

YAN Rongyia,HE Xiaoa,b,ZHOU Donghuaa,b. Robust Detection of Intermittent Faults of Linear Discrete-Time Stochastic Systems[J]. Journal of Shanghai Jiaotong University, 2015, 49(06): 812-818.

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