Distributed model predictive control of process networks: Impact of control architecture

Abstract This paper investigates the impact of control architecture design on the distributed model predictive control (MPC) of nonlinear complex process networks. A sequential distributed MPC structure is synthesized to regulate a nonlinear system whose dynamics are decomposed into multiple subsystems by community detection methods. The closed-loop performance and computational effort of employing centralized and sequential distributed MPC structures is analyzed for a reactor-separator integrated process.

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