Robust Fault Diagnosis of Networked Discrete Event Systems Using Labeled Petri Nets

The fault diagnosis problem in discrete event systems consists in detecting the occurrences of faults in a plant, which is essential for ensuring the reliability of the plant. In the literature, this problem has been widely studied by assuming that the communications between a plant and a diagnostic agent, i.e., a diagnoser, are reliable and instantaneous. However, for a networked system, the information generated by a plant is transmitted through a shared communication network such that communication delays and losses are inevitable. This article formulates and studies the fault diagnosis problem in networked discrete event systems (NDESs) modeled by labeled Petri nets, where communication delays and losses are considered. Such a problem is also called <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">robust fault diagnosis</i> in this article. An important notion closely related to robust diagnosis, named <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">networked diagnosability</i>, is introduced, indicating that any occurred fault in a NDES is definitely determined after a limited number of observations. For a NDES, a tool called a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">networked basis diagnoser</i> is excogitated to solve the robust diagnosis problem. A necessary and sufficient condition for verifying the networked diagnosability of a plant is derived by using the developed diagnoser. Finally, a manufacturing system is presented to illustrate the developed approach.

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Publication Details

Journal
IEEE Transactions on Systems Man and Cybernetics Systems
Published
2025-06-19
DOI
https://doi.org/10.1109/tsmc.2025.3573565
Citations
5
Primary Topic
Petri Nets in System Modeling
Type
article
Field-Weighted Citation Impact
7.52

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article

Robust Fault Diagnosis of Networked Discrete Event Systems Using Labeled Petri Nets

Ruotian Liu, Yihui Hu, Zhiwu Li, Maria Pia Fanti
5 citations
IEEE Transactions on Systems Man and Cybernetics Systems
Petri Nets in System Modeling
7.52
article

Robust Fault Diagnosis of Networked Discrete Event Systems Using Labeled Petri Nets

Ruotian Liu, Yihui Hu, Zhiwu Li, Maria Pia Fanti
article en
5 citations

Abstract

The fault diagnosis problem in discrete event systems consists in detecting the occurrences of faults in a plant, which is essential for ensuring the reliability of the plant. In the literature, this problem has been widely studied by assuming that the communications between a plant and a diagnostic agent, i.e., a diagnoser, are reliable and instantaneous. However, for a networked system, the information generated by a plant is transmitted through a shared communication network such that communication delays and losses are inevitable. This article formulates and studies the fault diagnosis problem in networked discrete event systems (NDESs) modeled by labeled Petri nets, where communication delays and losses are considered. Such a problem is also called <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">robust fault diagnosis</i> in this article. An important notion closely related to robust diagnosis, named <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">networked diagnosability</i>, is introduced, indicating that any occurred fault in a NDES is definitely determined after a limited number of observations. For a NDES, a tool called a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">networked basis diagnoser</i> is excogitated to solve the robust diagnosis problem. A necessary and sufficient condition for verifying the networked diagnosability of a plant is derived by using the developed diagnoser. Finally, a manufacturing system is presented to illustrate the developed approach.

IEEE Transactions on Systems Man and Cybernetics SystemsVol. 55(9)
Macau University of Science and Technology (MO), Xi’an University of Posts and Telecommunications (CN), Polytechnic University of Bari (IT)
National Natural Science Foundation of China, Science and Technology Development Fund, National Key Research and Development Program of China, Natural Science Basic Research Program of Shaanxi Province
Openalex Percentile: Top 3%
Petri Nets in System Modeling
7.52
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