Decentralized Diagnosis by Petri Nets and Integer Linear Programming

This paper proposes a novel decentralized on-line fault diagnosis approach based on the solution of some integer linear programming problems for discrete event systems in a Petri net framework. The decentralized architecture consists of a set of local sites communicating with a coordinator that deci...

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Veröffentlicht in:IEEE transactions on systems, man, and cybernetics. Systems Jg. 48; H. 10; S. 1689 - 1700
Hauptverfasser: Cong, Xuya, Fanti, Maria Pia, Mangini, Agostino Marcello, Li, Zhiwu
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.10.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Architecture
Automata
Communication
Computer architecture
Diagnostic systems
Discrete event systems
Discrete event systems (DESs)
Fault detection
Fault diagnosis
Integer linear programming
integer linear programming (ILP)
Integer programming
Linear programming
Petri nets
Petri nets (PNs)
Protocols
ISSN:2168-2216, 2168-2232
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Zusammenfassung:This paper proposes a novel decentralized on-line fault diagnosis approach based on the solution of some integer linear programming problems for discrete event systems in a Petri net framework. The decentralized architecture consists of a set of local sites communicating with a coordinator that decides whether the system behavior is normal or subject to some possible faults. To this aim, some results allow defining the rules applied by the coordinator and the local sites to provide the global diagnosis results. Moreover, two protocols for the detection and diagnosis of faults are proposed: they differ for the information exchanged between local sites and coordinator and the diagnostic capability. In addition, a sufficient and necessary condition under which the second presented protocol can successfully diagnose a fault in the decentralized architecture is proved. Finally, some examples are presented to show the efficiency of the proposed approach.
Bibliographie:ObjectType-Article-1
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ISSN:2168-2216
2168-2232
DOI:10.1109/TSMC.2017.2726108