Controlling reactors in distributed manufacturing processes producing different grades of a product requires intelligent reconfiguration strategies. Agent-based approaches are ideal for such cases, since they can provide flexible, robust, and emergent solutions during dynamically changing process conditions. A hierarchical, agent-based system with local and global control agents is developed to control networks of interconnected chemical reactors. This paper proposes a multilayered, multiagent framework based on a decentralized approach for the supervision of grade transitions in autocatalytic reactor networks. The values for the manipulated variables are chosen to give the least disturbance to the system. The case studies show that the approach is successful in controlling the reactor network and being able to keep the desired grade even after the need of shutting down some of the reactors.