Diagnosis of behaviors of interest in partially-observed discrete-event systems

Abstract In this paper, we address the problem of diagnosing the behaviors of interest in discrete-event systems. To this end, we introduce the notion of language-diagnosability, based on language specifications that generalizes diagnosability based on event specifications. A polynomial-time algorithm for verifying language-diagnosability is developed. Building upon the verification algorithm, we develop a polynomial-time algorithm for computing the worst case detection delay of a given system. The computation of the worst case detection delay involves the shortest path computation of a weighted, directed graph. We exploit a special weighting structure of the graph resulting from the verification algorithm, which enables an algorithm with a lower complexity than the commonly used Bellman–Ford shortest path algorithm.