An Efficient Algorithm for K-Diagnosability Analysis of Bounded and Unbounded Petri Nets

被引：0
|
作者：
Chouchane, A. [1 ]
Ghazel, M. [1 ]
机构：
[1] Univ Gustave Eiffel, COSYS ESTAS, Lille Campus, F-59650 Villeneuve Dascq, France
来源：
IFAC PAPERSONLINE | 2024年 / 58卷 / 01期
关键词：
K-diagnosability; bounded and unbounded labeled Petri nets; discrete event systems; linear optimization technique;
D O I：
10.1016/j.ifacol.2024.07.028
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
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 condition for K-diagnosability by addressing the relaxation (in R) of an Integer Linear Programming (ILP) problem defined on a compacted horizon. In addition, if the model is K-diagnosable, the technique provides a value K-relax, potentially lower than K, that ensures (K-relax-)diagnosability. To assess the performance and efficiency of the developed method, a Petri net model of a railway benchmark is investigated.
引用
收藏
页码：162 / 167
页数：6
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