Probabilistic fault diagnosis in discrete event systems

Xi Wang, Ishanu Chattopadhyay, Asok Ray

Research output: Contribution to journalConference articlepeer-review

7 Scopus citations


This paper presents a concept of discrete-event probabilistic fault diagnosis as an extension of the binary decision approach proposed by Sampath et al., where unobservable failure events are included in the representation of the system behavior under both normal and faulty conditions. It is assumed that the probability of each transition is known at the time of decision making. Based on this finite-state automaton model, probabilistic reasoning is applied for on-line diagnosis of dynamical systems. The major advantage of this approach is early detection of multi-component faults, which facilitates robust reconfiguration of the decision and control system.

Original languageEnglish (US)
Article numberFrB06.5
Pages (from-to)4794-4799
Number of pages6
JournalProceedings of the IEEE Conference on Decision and Control
StatePublished - 2004
Event2004 43rd IEEE Conference on Decision and Control (CDC) - Nassau, Bahamas
Duration: Dec 14 2004Dec 17 2004

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization


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