Decentralized Failure Diagnosis of Stochastic Discrete Event Systems
  Recently, the diagnosability of {\it stochastic discrete event systems}
(SDESs) was investigated in the literature, and, the failure diagnosis
considered was {\it centralized}. In this paper, we propose an approach to {\it
decentralized} failure diagnosis of SDESs, where the stochastic system uses
multiple local diagnosers to detect failures and each local diagnoser possesses
its own information. In a way, the centralized failure diagnosis of SDESs can
be viewed as a special case of the decentralized failure diagnosis presented in
this paper with only one projection. The main contributions are as follows: (1)
We formalize the notion of codiagnosability for stochastic automata, which
means that a failure can be detected by at least one local stochastic diagnoser
within a finite delay. (2) We construct a codiagnoser from a given stochastic
automaton with multiple projections, and the codiagnoser associated with the
local diagnosers is used to test codiagnosability condition of SDESs. (3) We
deal with a number of basic properties of the codiagnoser. In particular, a
necessary and sufficient condition for the codiagnosability of SDESs is
presented. (4) We give a computing method in detail to check whether
codiagnosability is violated. And (5) some examples are described to illustrate
the applications of the codiagnosability and its computing method.
