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Variable reasoning and analysis about uncertainty with fuzzy Petri nets

  • Tiehua Cao
  • Arthur C. Sanderson
Full Papers
Part of the Lecture Notes in Computer Science book series (LNCS, volume 691)

Abstract

Ordinary Petri nets often do not have sufficient power to represent and handle approximate and uncertain information. Fuzzy Petri nets are defined in this paper using three types of fuzzy variables: local fuzzy variables, fuzzy marking variables, and global fuzzy variables. These three types of variables are used to model uncertainty based on different aspects of fuzzy information. Several basic types of fuzzy Petri nets are analyzed, and the necessary and/or sufficient conditions of boundedness, liveness, and reversibility are given. An example of modeling sensory transitions in a robotic system is discussed to illustrate reasoning about input local fuzzy variables to obtain mutually exclusive tokens in the output places.

Keywords

Fuzzy Variable Input Place Output Place Firing Rule Reasoning Function 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1993

Authors and Affiliations

  • Tiehua Cao
    • 1
  • Arthur C. Sanderson
    • 1
  1. 1.Electrical, Computer, and Systems Engineering DepartmentRensselaer Polytechnic InstituteTroyUSA

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