Conditional Petri Nets to Analyze and Simulate Automated Guided Vehicle System

Abstract

To examine the characteristics of various complex discrete event and distributed systems, Petri net is a potential mathematical and graphical modeling tool. The fuzzy production propositions of automated guided vehicle systems are represented in this paper using a variant of the Petri net known as the fuzzy Petri net (FPN), in which propositions explains the relation between two propositions. Due to its relevance in practice, another Petri net variant known as Conditional Petri net (CPN) is taken into consideration for this purpose. CPNs can be used to qualitatively describe gene regulatory interactions, to represent the active and inactive stages of a system like switching circuits, etc. The obtained truth degree of the success node validates the belief strength of this property, which is a crucial property of BPNs based on initial marking of Petri nets.