Deadlock prediction and avoidance based on Petri nets for zone-control automated guided vehicle systems

Deadlock problems of zone-control uni-directional automated guided vehicle (AGV) systems are discussed in this paper. Deadlocks of two types in such AGV systems are first classified from the perspective of shared resources, i.e. guide-path zones and buffers. A special class of Petri nets, attributed Petri nets (APN), is defined and used to represent the current state and to generate future states of zone-control AGV systems. We propose an algorithmic procedure to predict in real time and to avoid deadlocks that are caused by sharing guide-path zones in zone-control AGV systems. The proposed algorithm utilizes the current system state and future predicted states to avoid deadlocks. These states are obtained and generated from the obtained APN. A modular approach is employed to facilitate the construction of APN models of zone-control AGV systems.

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