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Network‐based fault detection for discrete‐time state‐delay systems: A new measurement model
Author(s) -
He Xiao,
Wang Zidong,
Ji Y. D.,
Zhou D. H.
Publication year - 2008
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/acs.1000
Subject(s) - control theory (sociology) , dropout (neural networks) , filter (signal processing) , fault (geology) , computer science , fault detection and isolation , state (computer science) , discrete time and continuous time , markov chain , bounded function , algorithm , mathematics , actuator , statistics , control (management) , mathematical analysis , machine learning , artificial intelligence , seismology , computer vision , geology
In this paper, the fault detection problem is studied for a class of discrete‐time networked systems with multiple state delays and unknown input. A new measurement model is proposed to account for both the random measurement delays and the stochastic data missing (package dropout) phenomenon, which are typically resulted from the limited capacity of the communication networks. At any time point, one of the followingcases (random events) occurs: measurement missing case, no time‐delay case, one‐step delay case, two‐step delay case, …, q ‐step delay case. The probabilistic switching between different cases is assumed to obey a homogeneous Markovian chain. We aim to design a fault detection filter such that, for all unknown input and incomplete measurements, the error between the residual and weighted faults is made as small as possible. The addressed fault detection problem is first converted into an auxiliary H ∞ filtering problem for a certain Markovian jumping system (MJS). Then, with the help of the bounded real lemma of MJSs, a sufficient condition for the existence of the desired fault detection filter is established in terms of a set of linear matrix inequalities (LMIs). A simulation example is provided to illustrate the effectiveness and applicability of the proposed techniques. Copyright © 2007 John Wiley & Sons, Ltd.