Knowledge-Based Intelligent Information and Engineering Systems

Volume 4252 of the series Lecture Notes in Computer Science pp 879-887

An Intelligent Technique Based on Petri Nets for Diagnosability Enhancement of Discrete Event Systems

  • YuanLin WenAffiliated withDepartment of Electrical Engineering, National Taiwan Ocean University
  • , MuDer JengAffiliated withDepartment of Electrical Engineering, National Taiwan Ocean University
  • , LiDer JengAffiliated withDepartment of Electrical Engineering, Chung-Yuan Christian University
  • , Fan Pei-ShuAffiliated withCollege of Mechanica and Electrical Engineering, National Taipei University of Technology

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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.