On a maximally permissive deadlock prevention policy for automated manufacturing systems by using resource-oriented Petri nets.

It is theoretically and practically significant to synthesize a maximally permissive (optimal) controller to prevent deadlocks in an automated manufacturing system (AMS). With an AMS being modeled with Petri nets, by the existing methods, integer linear programming (ILP) problems are usually formulated and solved to obtain optimal policies by forbidding illegal markings at the same time no legal marking is excluded. Without an efficient technique for solving an ILP, such a method is usually computationally prohibitive. A resource-oriented Petri net (ROPN) is employed to model a class of AMS for resolving the deadlock control problem with maximal permissiveness in this paper. Efficient methods are developed to figure out the key structures in an ROPN model for deadlock prevention. Based on the structural properties of ROPN models, this work explores several types of illegal markings that can be prohibited optimally by structural analysis. For these markings, a deadlock prevention policy can be derived in an algebraic way without solving a notorious ILP problem. For the other markings, linear programming (LP), instead of ILP, approaches are developed to forbid them optimally. Thus, a maximally permissive controller can be developed while the computational cost is reduced greatly. The proposed methods are verified by typical examples in the literature.