Threshold computation for fault detection in linear discrete‐time Markov jump systems |
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| Authors: | Jedsada Saijai Steven X Ding Ali Abdo Bo Shen Waseem Damlakhi |
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| Affiliation: | Institute for Automatic Control and Complex Systems (AKS), Faculty of Engineering, University of Duisburg‐Essen, Duisburg 47057, Germany |
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| Abstract: | This paper proposes a threshold computation scheme for an observer‐based fault detection (FD) in linear discrete‐time Markovian jump systems. An observer‐based FD scheme typically consists of two stages known as residual generation and residual evaluation. Even information of faults is contained inside a residual signal, a decision of faults occurrence is consequently made by a residual evaluation stage, which consists of residual evaluation function and threshold setting. For this reason, a successful FD strongly depends on a threshold setting for a given residual evaluation function. In this paper, Kalman filter (KF) is used as a residual generator. Based on an accessibility of Markov chain to KF, two types of residual generations are considered, namely mode‐dependent and mode‐independent residual generation. After that threshold is computed in a residual evaluation stage such that a maximum fault detection rate is achieved, for a given false alarm rate. Without any knowledge of a probability density function of residual signal before and after fault occurrence, a threshold is computed by using an estimation of residual evaluation function variance in a fault‐free case. Finally, a detection performance is demonstrated by a numerical example. Copyright © 2013 John Wiley & Sons, Ltd. |
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| Keywords: | fault detection linear Markov jump systems Markov chain residual evaluation threshold computation |
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