Maximally Permissive Distributed Control of Large Scale Automated Manufacturing Systems Modeled with Petri Nets

Ensuring nonblockingness remains challenging for automated manufacturing systems (AMSs) owing to their discrete event dynamics. Both scalability and maximal permissiveness are essential for the synthesis and implementation of their centralized supervisors. Inspired by the divide and conquer philosophy, this brief proposes a partition methodology and distributed control technique for large-scale AMSs. They are represented as interconnected and overlapping subsystems sharing some common components in terms of buffers. For each subsystem, a local supervisor is designed based on its local behavior and neighboring information only. Generalizing the existing results, we develop a condition under which the control law via decomposition promises the maximal permissiveness. Buffer capacities are well designed for the sake of their decomposition into multiple overlapping subsystems. Theoretical results are developed to characterize the behavior compatibility among local controllers. An experimental study illustrates the effectiveness of the proposed method.