This paper applies distributed artificial intelligence to the real-time planning and control of flexible manufacturing systems (FMS) consisting of asynchronous manufacturing cells. A knowledge-based approach is used to determine the course of action, resource sharing, and processor assignments. Within each cell there is an embedded automatic planning system that executes dynamic scheduling and supervises manufacturing operations. Because of the decentralized control, realtime task, assignments are carried out by a negotiation process among cell hosts.The negotiation process is modeled by augmented Petri nets -the combination of production rules and Petri nets -and is executed by a distributed, rule-based algorithm.