Optimal Petri-Net Controller for Avoiding Collisions in a Class of Automated Guided Vehicle Systems

Abstract

Automated guided vehicles (AGVs) are being extensively used for transportation and distribution of materials due to their high-efficiency. However, the vehicle-collision free problem is challenging since, when modeling these systems, there are indistinguishable and uncontrollable events due to the limited sensors and actuators. This paper proposes an approach to the design of a maximally permissive (optimal) controller to prevent vehicles from any collision based on Petri nets (PNs). For a typical class of AGV systems, a system modeling algorithm is presented using labeled PN, where indistinguishable events are represented by a set of transitions carrying the same label, and an uncontrollable event by an uncontrollable transition. By virtue of the PN model, the collision-free problem is formalized as a conjunction of linear constraints that are converted into admissible ones by an algorithm such that the computational overhead due to uncontrollable events is significantly reduced. In turn, a method is developed to compute the set of consistent markings for an observed sequence of labels that represent signals generated by sensors. Finally, given an observed sequence, a maximally permissive control action is computed to enforce a conjunction of admissible linear constraints based on the set of consistent markings. The approach well addresses the challenging issues caused by indistinguishable and uncontrollable events. A typical AGV system is utilized to illustrate and verify the theoretical results throughout the work.