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Estimation et diagnostic de réseaux de Petri partiellement observables

Abstract : With the evolution of technology, humans have made available systems increasingly complex but also increasingly sensitive to faults that may affect it. A diagnostic procedure which contributes to the smooth running of the process is thus necessary. In this context, the aim of this thesis is the diagnosis of discrete event systems modeled by partially observed Labeled Petri Nets (LPNs). Under the assumption that each defect is modeled by the firing of an unobservable transition, two diagnostic approaches based on state estimation are developed. A first approach is to estimate the set of basis markings on a sliding elementary horizon. This approach is carried out in two steps. The first step is to determine a set of candidate vectors from an algebraic approach. The second step is to eliminate the calculated candidate solutions that are not associated with a possible trajectory of the LPN. As the set of basis markings can also be huge, a second diagnostic approach will avoid this pitfall by not estimating the markings. A relaxation technique of Integer Linear Programming (ILP) problems on a receding horizon is used to have a diagnosis in polynomial time.
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Submitted on : Tuesday, October 15, 2019 - 9:23:07 AM
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  • HAL Id : tel-02316020, version 1


Amira Dardour. Estimation et diagnostic de réseaux de Petri partiellement observables. Automatique. Université d'Angers; École nationale d'ingénieurs de Sfax (Tunisie), 2018. Français. ⟨NNT : 2018ANGE0054⟩. ⟨tel-02316020⟩



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