We propose an algebraic approach to investigate K-diagnosability of partially observed
labeled Petri nets which can be either bounded or unbounded. Namely, a necessary and …

Diagnosability of faults in discrete event systems modeled with Petri nets can be assessed
either via graph-based techniques (also called diagnoser, verifier/twin-plant based …

In this paper, we design an efficient diagnosis technique for partially observed discrete event
systems modeled by labeled Petri nets. The fault detection is based on analytical …

In this paper, we propose a polynomial algorithm for conducting K-diagnosability analysis on
both bounded and unbounded labeled Petri nets. More specifically, we formulate a sufficient …

Functional safety is crucial for Electric Vehicles (EVs) as it ensures that the EV systems
operate correctly and safely. This paper aims to propose an efficient and holistic approach to …

Many diagnosis approaches for discrete event systems are diagnoser-based. A diagnoser is
a deterministic automaton that can be built directly from the underlying system model by …

In this article, fault diagnosis of hierarchical discrete event systems (HDES) is investigated
using state-tree structures (STS). As a structured formalism, an STS provides a compact …

This paper deals with a benchmark-based experimental comparison of three diagnose-
based approaches for fault diagnosis of discrete event systems modeled by Petri nets: the …

In this paper, we present a diagnoser‐based approach to deal with fault diagnosis of
bounded labeled Petri nets. The approach consists in building a semi‐symbolic diagnoser to …

Fault diagnosis and prediction for complex control systems rely either on the collection of
rich data for training neural networks or on the system models and prior knowledge of faults …