A framework for on-line passive fault diagnosis in discrete-event systems is proposed. In this approach, the system and the diagnoser (the fault detection system) do not have to be initialized at the same time, and no information about the state or even the condition (failure status) of the system before the initiation of diagnosis is required.; First, a state-based approach for fault diagnosis in finite-state automata is presented. The design of the fault detection system has, in the worst case, exponential time complexity. A model reduction scheme with Polynomial time complexity is introduced to reduce the computational Complexity of the design. Next the use of timing information to improve the accuracy of diagnosis is considered. Instead of directly extending the framework to timed discrete-event systems, an alternative approach is taken which leads to significant reduction in on-line computing requirements, and in many cases, in the size of the diagnoser at the expense of more off-line design calculations. The issue of diagnosability of failures in this framework is also studied and necessary and sufficient conditions for diagnosability are derived.; In addition, the cases where the discrete-event models used in fault issue is whether the discrete-event model contains enough information about the system for the purpose of fault diagnosis. In this regard, two different notions of consistency between high-level (discrete-event) and low-level (hybrid) models are introduced. Sufficient conditions for consistency are derived and a semi-algorithmic method for constructing suitable high-level discrete-event models from low-level hybrid systems is developed.
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