A Set Covering Approach to Design Maximally Permissive Supervisors for Flexible Manufacturing Systems - Yongyao Li; Yufeng Chen; Rui Zhou (Mathematics, 2024)
The supervisory control of Petri nets aims to enforce the undesired behavior as unreachable by designing a set of control places. This work presents a set cover approach to design maximally permissive supervisors. For each first-met bad marking, an integer linear programming problem is developed to obtain a control place to prohibit it. An objective function is formulated to make the maximal number of first-met bad markings forbidden. Then, we develop a set covering approach to minimize the number of selected control places. The proposed approach can guarantee the maximal permissiveness of the obtained supervisor and provide a trade-off between structural complexity and computational cost. Several examples are considered to validate the proposed method.