Robust Fault Diagnosis Against Permanent Loss of Observations Using Labeled Petri Nets
研究了离散事件系统中部分标签可能永久不可观测时的鲁棒故障诊断问题，提出基于标签Petri网的新概念和诊断方法，确保诊断结果正确。
This study tackles the challenge of robust fault diagnosis in discrete event systems (DESs) that experience permanent observation losses using labeled Petri nets (LPNs). We consider the scenario that the initially observable transitions may become unobservable before their firings. Especially, the case that some, instead of all, of the transitions with a shared label may become unobservable is also taken into account. In such a scenario, the diagnosers in the existing methods may not report correct diagnostic results. This article presents a novel notion to ensure robust diagnosability for LPNs, aimed at overcoming the issue of permanent observation loss. To avert enumerating all the reachable markings, a structure called a tagged basis reachability graph (t-BRG) is developed, based on which all subsets of observable transitions, called diagnosis transition sets (DTSs), that ensure the diagnosability of the plant independently are calculated. Then, a special class of verifiers to assess the robust diagnosability of a system experiencing permanent observation loss is developed. Finally, an online diagnosis method performed by a set of diagnosers is presented and demonstrated by examples.