A Generalized Inference-Based Prognosis Framework for Discrete Event Systems. Issue 1 (July 2017) - Takai, Shigemasa; Kumar, Ratnesh
Abstract: We previously introduced an inference-based framework for decentralized prognosis of discrete event systems, and formulated the notion of N-inference V-prognosability to characterize the existence of a disjunctive decentralized prognosis scheme such that any fault can be predicted prior to its occurrence by at least one of the prognosers, using at most N-levels of inferencing. While the disjunctive scheme relies on one of the prognosers making a positive decision, the dual conjunctive scheme relies on none of the prognosers making a negative decision. It is known that the two schemes are incomparable, and in this paper we extend our earlier work to provide a more general framework, by introducing a notion of N-inference prognosability, that captures both disjunctive and conjunctive schemes. We also develop a method for verifying N-inference prognosability.