Robust diagnosis of discrete-event systems subject to permanent sensor failures

Abstract One approach to online fault diagnosis of discrete-event systems is through the use of the diagnosers . Diagnosers are deterministic automata whose states are sets formed with the states of the plant together with labels that indicate if the trace that has occurred so far possesses or not the fault event. The decision regarding fault occurrence is taken based solely on observable events, i.e. , events whose occurrences can be recorded by sensors. However, if one or more sensors that provide information on event occurrences fail, the diagnoser may either come to a halt or may even provide wrong information regarding fault occurrence. In order to overcome this deficiency, this paper proposes a robust diagnoser that deploys the redundancy that may exist in a set formed of diagnosis bases (set of events that guarantee fault diagnosability) with a view to ensure the fault diagnosis even in the occurrence of permanent sensor failures.