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

This is the authors' abstract. We don't add key points for this paper.

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 robust fault diagnosis in this article. An important notion closely related to robust diagnosis, named networked diagnosability, 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 networked basis diagnoser 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.