An Efficient Fault Diagnosis Approach Based on Integer Linear Programming for Labeled Petri Nets
Guanghui Zhu, Lei Feng, Zhiwu Li, Naiqi Wu
Abstract
In this article, we present a fault diagnosis approach for discrete event systems using labeled Petri nets. In contrast to the existing works, a new fault class containing all the fault transitions is additionally introduced in the diagnosis function, leading to a more informative and precise diagnosis result. An integer linear programming (ILP) problem is built according to an observed word. By specifying different objective functions to the ILP problem, the diagnosis result is obtained without enumerating all observable transition sequences consistent with the observed word, which is more efficient in comparison with the existing ILP-based approaches.
Topics & Concepts
Petri netInteger programmingFault (geology)Word (group theory)Integer (computer science)Linear programmingComputer scienceEvent (particle physics)ObservableAlgorithmClass (philosophy)Function (biology)Theoretical computer scienceMathematicsArtificial intelligenceProgramming languagePhysicsGeologySeismologyEvolutionary biologyBiologyQuantum mechanicsGeometryPetri Nets in System ModelingFlexible and Reconfigurable Manufacturing SystemsFormal Methods in Verification