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Article Dans Une Revue Automatica Année : 2023

K-diagnosability analysis of bounded and unbounded Petri nets using linear optimization

Résumé

We propose an algebraic approach to investigate K -diagnosability of partially observed labeled Petri nets which can be either bounded or unbounded. Namely, a necessary and sufficient condition for K-diagnosability is established based on the resolution of an Integer Linear Programming (ILP) problem. When the system is K -diagnosable, our approach also yields the minimal value K min ? K that ensures K min -diagnosability. The value of K min is calculated directly, using the same ILP formulation, i.e, without testing 1 , . . . , (K min ? 1)-diagnosability. A second K -diagnosability approach, which is derived from the first one, is also developed on a compacted horizon providing a sufficient condition for K-diagnosability. This second technique allows for reducing the system dimensionality yielding a higher computational efficiency and allowing the characterization of the length of the sequences that lead to the fault occurrence, which is necessary to perform the K -diagnosability test of the first approach.
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Dates et versions

hal-03842331 , version 1 (11-09-2023)

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Amira Chouchane, Mohamed Ghazel, Abderraouf Boussif. K-diagnosability analysis of bounded and unbounded Petri nets using linear optimization. Automatica, 2023, 147, pp1-13. ⟨10.1016/j.automatica.2022.110689⟩. ⟨hal-03842331⟩
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