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Communication Dans Un Congrès Année : 2017

Diagnosability Degree of Stochastic Discrete Event Systems

Résumé

— Diagnosability is the ability to detect a fault from partial observations collected on a system. It has been studied for numerous models of discrete event systems, but essentially from a logical perspective. This paper explores quantitative versions of the problem, to evaluate " how much " a system is (non-)diagnosable. For the diagnosable part of a system, that we characterize, we then examine the probability distribution of the detection delay. We show that the mean and the standard deviation of the detection delay can be easily evaluated.
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Dates et versions

hal-01651232 , version 1 (28-11-2017)

Identifiants

  • HAL Id : hal-01651232 , version 1

Citer

Hugo Bazille, Eric Fabre, Blaise Genest. Diagnosability Degree of Stochastic Discrete Event Systems. CDC 2017 - 56th IEEE Conference on Decision and Control, Dec 2017, Melbourne, Australia. pp.5726-5731. ⟨hal-01651232⟩
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