Predictability analysis of distributed discrete event systems

Abstract

Predictability is an important system property that determines with certainty the future occurrence of a fault based on a model of the system and a sequence of observations. The existing works dealt with predictability analysis of discrete-event systems in the centralized way. To deal with this important problem in a more efficient way, in this paper, we first propose a new centralized polynomial algorithm, which is inspired from twin plant method for diagnosability checking and more importantly, is adaptable to a distributed framework. Then we show how to extend this algorithm to a distributed one, based on local structure. We first obtain the original predictability information from the faulty component, and then check its consistency in the whole system to decide predictability from a global point of view. In this way, we avoid constructing global structure and thus greatly reduce the search space.