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Title: Diagnosis on a sliding window for partially observable Petri nets (English)
Author: Chouchane, Amira
Author: Declerck, Philippe
Language: English
Journal: Kybernetika
ISSN: 0023-5954 (print)
ISSN: 1805-949X (online)
Volume: 58
Issue: 4
Year: 2022
Pages: 479-497
Summary lang: English
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Category: math
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Summary: 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. (English)
Keyword: diagnosis
Keyword: state estimation
Keyword: partially observed Petri net
Keyword: sliding window
Keyword: integer linear programming
MSC: 49Kxx
MSC: 93Axx
idZBL: Zbl 07655843
idMR: MR4521852
DOI: 10.14736/kyb-2022-4-0479
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Date available: 2022-12-02T13:07:15Z
Last updated: 2023-03-13
Stable URL: http://hdl.handle.net/10338.dmlcz/151160
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