Geodesic
Diagnosis on a sliding window for partially observable Petri nets
Kybernetika, Tome 58 (2022) no. 4, pp. 479-497 Cet article a éte moissonné depuis la source Czech Digital Mathematics Library

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In this paper, we propose an algebraic approach to investigate the diagnosis of partially observable labeled Petri nets based on state estimation on a sliding window of a predefined length $h$. Given an observation, the resulting diagnosis state can be computed while solving integer linear programming problems with a reduced subset of basis markings. The proposed approach consists in exploiting a subset of $h$ observations at each estimation step, which provides a partial diagnosis relevant to the current observation window. This technique allows a status update with a "forgetfulness" of past observations and enables distinguishing repetitive and punctual faults. The complete diagnosis state can be defined as a function of the partial diagnosis states interpreted on the sliding window. As the analysis shows that some basis markings can present an inconsistency with a future evolution, which possibly implies unnecessary computations of basis markings, a withdrawal procedure of these irrelevant basis markings based on linear programming is proposed.
In this paper, we propose an algebraic approach to investigate the diagnosis of partially observable labeled Petri nets based on state estimation on a sliding window of a predefined length $h$. Given an observation, the resulting diagnosis state can be computed while solving integer linear programming problems with a reduced subset of basis markings. The proposed approach consists in exploiting a subset of $h$ observations at each estimation step, which provides a partial diagnosis relevant to the current observation window. This technique allows a status update with a "forgetfulness" of past observations and enables distinguishing repetitive and punctual faults. The complete diagnosis state can be defined as a function of the partial diagnosis states interpreted on the sliding window. As the analysis shows that some basis markings can present an inconsistency with a future evolution, which possibly implies unnecessary computations of basis markings, a withdrawal procedure of these irrelevant basis markings based on linear programming is proposed.
DOI : 10.14736/kyb-2022-4-0479
Classification : 49Kxx, 93Axx
Keywords: diagnosis; state estimation; partially observed Petri net; sliding window; integer linear programming 
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     title = {Diagnosis on a sliding window for partially observable {Petri} nets},
     journal = {Kybernetika},
     pages = {479--497},
     year = {2022},
     volume = {58},
     number = {4},
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     language = {en},
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Chouchane, Amira; Declerck, Philippe. Diagnosis on a sliding window for partially observable Petri nets. Kybernetika, Tome 58 (2022) no. 4, pp. 479-497. doi: 10.14736/kyb-2022-4-0479

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