Intersection based decentralized diagnosis: Implementation and verification

We consider decentralized diagnosis in discrete event systems that are modeled as non-deterministic finite automata and are observed, through distinct natural projection maps, at multiple observation sites. Specifically, we consider a scenario where two or more observers (each with its own map) are allowed to communicate their assessments (state estimates and matching normal/failure conditions) to a centralized location which then makes an overall decision based on the intersection of the local state estimates and their matching conditions. This intersection based decentralized diagnosis (IBDD) scheme can be implemented with polynomial complexity, both at the observation sites and at the centralized location. It is shown that IBDD can be verified with an algorithm of polynomial complexity that constructs verifiers for the observation sites, and analyzes properties of their parallel composition and product with the system.