Codiagnosability of networked discrete event systems subject to communication delays and intermittent loss of observation

• Published in: Discrete event dynamic systems Vol. 28; no. 2; pp. 215 - 246
• Main Authors: Nunes, Carlos E. V., Moreira, Marcos V., Alves, Marcos V. S., Carvalho, Lilian K., Basilio, João Carlos
• Format: Journal Article
• Language: English
• Published: New York Springer US 01-06-2018; Springer Nature B.V
• Subjects: Communication; Communication networks; Communications systems; Control; Convex and Discrete Geometry; Diagnosis; Discrete event systems; Electrical Engineering; Electronic devices; Human communication; Machines; Manufacturing; Mathematics; Mathematics and Statistics; Opacity and Supervisory Control of Discrete Event Systems; Operations Research/Decision Theory; Processes; Special Issue on Diagnosis; Systems Theory; Automaton; Language codiagnosability; Communication delays; Networked discrete-event systems
• ISSN: 0924-6703; 1573-7594
• DOI: 10.1007/s10626-017-0265-6

Failure diagnosis is a crucial task in modern industrial systems, and several works in the literature address this problem by modeling the system as a Discrete-Event System (DES). Most of them assume perfect communication between sensors and diagnosers,
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., no loss of observation of events, or event communication delays between the measurement sites and the diagnosers. However, industrial systems can be large and physically distributed, in which cases, communication networks are used to provide an efficient way to establish communication between devices. In diagnosis systems, the use of networks can introduce delays in the communication of event occurrences from measurement sites to the local diagnosers, leading to an incorrect observation of the order of occurrence of events generated by the system and, as a consequence, to an incorrect diagnosis decision by the local diagnoser. In this paper, we address the problem of decentralized diagnosis of networked Discrete-Event Systems subject to event communication delays, and we introduce the definition of network codiagnosability of the language generated by a DES subject to both event communication delays and intermittent loss of observation, and present necessary and sufficient conditions for a language to be network codiagnosable, for short. We also propose an algorithm to verify this property.