An intelligent technique based on petri nets for diagnosability enhancement of discrete event systems

  • Authors:

  • YuanLin Wen;MuDer Jeng;LiDer Jeng;Fan Pei-Shu

  • Affiliations:

  • Department of Electrical Engineering, National Taiwan Ocean University, Keelung, Taiwan;Department of Electrical Engineering, National Taiwan Ocean University, Keelung, Taiwan;Department of Electrical Engineering, Chung-Yuan Christian University, Chung-Li, Taiwan;College of Mechanica and Electrical Engineering, National Taipei University of Technology, Taipei, Taiwan

  • Venue:
  • KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part II
  • Year:
  • 2006

Quantified Score

Hi-index 0.00

Visualization

Abstract

This paper presents an intelligent systematic methodology for enhancing diagnosability of discrete event systems by adding sensors. The methodology consists of the following iteractive steps. First, Petri nets are used to model the target system. Then, an algorithm of polynomial complexity is adopted to analyze a sufficient condition of diagnosability of the modeled system. Here, diagnosability is defined in the context of the discrete event systems theory, which was first introduced by Sampath [3]. If the system is found to be possibly non-diagnosable, T-components of the Petri net model are computed to find a location in the system for adding a sensor. The objective is to distinguish multiple T-components with the same observable event sequences. The diagnosability-checking algorithm is used again to see if the system with the newly added sensor is diagnosable. The process is repeated until either the system is diagnosable or diagnosability of the system cannot be enhanced.