Control of grade transitions in distributed chemical reactor networks—An agent-based approach

Supervision of distributed manufacturing processes producing different grades of a product requires intelligent reconfiguration strategies during grade transition phases to minimize off-spec production. Agent-based approaches are ideal for such problems and they provide flexible, robust, and emergent solutions during dynamically changing process conditions. Three different multi-layered, multi-agent frameworks are proposed for the supervision of grade transitions in autocatalytic reactor networks. The first framework is the centralized framework and it is useful for small-scale grade transitions where only a small region of the network needs to be reconfigured. Alternatively, the other two frameworks use a decentralized approach. The first decentralized framework implements genetic algorithms and the second one uses self-organizing heuristics and auctions for large-scale grade transitions. The case studies demonstrate that as the complexity of the reconfiguration problem increases, decentralized solutions perform more efficiently.     

A multi-agent approach using perceptron-based learning for robust operation of distributed chemical reactor networks

Controlling the individual reactors of a chemical reactor network producing different grades of a product requires intelligent reconfiguration strategies. Agent-based approaches are ideal for such distributed manufacturing processes, since they provide flexible, robust, and emergent solutions under dynamically changing process conditions. This paper proposes a multi-layered, multi-agent framework based on a decentralized online learning approach for the supervision of grade transitions in autocatalytic reactor networks. The values for the manipulated variables and the path to the target reactor are determined to give the least disturbance to the system. Case studies illustrate the performance of the approach in managing grade transition and disturbance rejection in a reactor network.