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Erschienen in:
2005 | OriginalPaper | Buchkapitel
Fault Diagnosis Using Timed Automata
verfasst von : Patricia Bouyer, Fabrice Chevalier, Deepak D’Souza
Erschienen in: Foundations of Software Science and Computational Structures
Verlag: Springer Berlin Heidelberg
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Fault diagnosis consists in observing behaviours of systems, and in detecting
online
whether an error has occurred or not. In the context of discrete event systems this problem has been well-studied, but much less work has been done in the timed framework. In this paper, we consider the problem of diagnosing faults in behaviours of timed plants. We focus on the problem of synthesizing fault diagnosers which are realizable as deterministic timed automata, with the motivation that such diagnosers would function as efficient online fault detectors. We study two classes of such mechanisms, the class of deterministic timed automata (DTA) and the class of event-recording timed automata (ERA). We show that the problem of synthesizing diagnosers in each of these classes is decidable, provided we are given a bound on the resources available to the diagnoser. We prove that under this assumption diagnosability is 2EXPTIME-complete in the case of DTA’s whereas it becomes PSPACE-complete for ERA’s.