Reduction Rules for Diagnosability Analysis of Complex Systems Modeled by Labeled Petri Nets
| Autor: | Manel Khlif-Bouassida, Ben Li, Armand Toguyeni |
|---|---|
| Přispěvatelé: | Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Centrale Lille |
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
0209 industrial biotechnology
Theoretical computer science Computer science Complex system 02 engineering and technology Petri net Fault (power engineering) Unobservable Reduction (complexity) 020901 industrial engineering & automation Control and Systems Engineering Bounded function [INFO.INFO-AU]Computer Science [cs]/Automatic Control Engineering A priori and a posteriori [INFO]Computer Science [cs] Electrical and Electronic Engineering Combinatorial explosion ComputingMilieux_MISCELLANEOUS |
| Zdroj: | IEEE Transactions on Automation Science and Engineering IEEE Transactions on Automation Science and Engineering, Institute of Electrical and Electronics Engineers, 2020, 17 (2), pp.1061-1069. ⟨10.1109/TASE.2019.2933230⟩ IEEE Transactions on Automation Science and Engineering, 2020, 17 (2), pp.1061-1069. ⟨10.1109/TASE.2019.2933230⟩ |
| ISSN: | 1545-5955 |
| DOI: | 10.1109/TASE.2019.2933230⟩ |
| Popis: | This article addresses the combinatorial explosion problem for diagnosability analysis of discrete event systems (DESs) using bounded labeled Petri nets (LPNs). Some reduction rules are given to simplify a priori the LPN model before analyzing the diagnosability. When the conditions of these reduction rules are fulfilled, some regular unobservable transitions and some specific observable transitions are suppressed. It is proven that these rules preserve the diagnosability property of the LPN system. By using reduction rules, the memory cost for diagnosability analysis is reduced. Note to Practitioners —Fault diagnosis based on discrete-event systems has been successfully used in several fields of applications, such as transportation, telecommunication, manufacturing, and so on. At the design stage of a system, the diagnosability needs to be held, which refers to the ability to determine if the system can detect the fault after its occurrence. Therefore, the diagnosability is a critical property due to its importance in terms of safety of an industrial system. In order to allow an industrial exploitation of diagnosability analysis, this article proposes reduction rules, which make it possible to reduce a priori the size of the LPN model of an industrial system. |
| Databáze: | OpenAIRE |
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