Robust diagnosability of discrete event systems subject to intermittent sensor failures

The modeling of physical systems using discrete event models assumes that a set of sensors always report the event occurrences correctly. However, bad sensor operation can result in loss of observability of the events associated with the malfunctioning sensors. If one or more sensors fail, it may be possible that either the diagnoser stands still or provide wrong information on the fault occurrence. This paper assumes that intermittent sensor failures may occur and deals with the problem of fault diagnosis in the presence of intermittent sensor failures. To this end, an automaton model for intermittent sensor failures based on a newly proposed language operation (language dilation) is presented in the paper. Necessary and sufficient conditions for robust diagnosability against intermittent sensor failure are also given in the paper. The development of a robust diagnoser that copes with intermittent sensor failures is another contribution of the paper.