Increasingly dynamic market conditions have fueled efforts to integrate scheduling and control in recent years. While a large number of formulations have been proposed for different control systems, the integration of scheduling and control for plants controlled by distributed MPC systems has received scant attention. In this article, we present a framework for the integration of scheduling and control for plants controlled by distributed MPC systems. We also propose strategies to approximately model the distributed MPC action within the integrated problem formulation, reducing its complexity and computation time. The integrated problem is solved at the dynamic real-time optimization (DRTO) level, in a moving horizon fashion, to compute set-points assigned to the lower-level distributed MPC subsystems, whose formulation is kept intact. Case study results suggest that these strategies can significantly reduce the solution time of the closed-loop integrated scheduling and control problem without severely impacting plant performance. We demonstrate that the proposed integrated scheduling and control formulation can successfully coordinate the MPC subsystems to meet market demands of distinct product grades, even in the presence of plant–model mismatch.

中文翻译：

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分布式MPC系统控制工厂的调度与控制集成


近年来，日益活跃的市场环境推动了调度和控制整合的努力。虽然针对不同的控制系统提出了大量的方案，但分布式 MPC 系统控制的工厂调度和控制的集成却很少受到关注。在本文中，我们提出了一个由分布式 MPC 系统控制的工厂的调度和控制集成框架。我们还提出了在集成问题表述中对分布式 MPC 动作进行近似建模的策略，从而降低其复杂性和计算时间。集成问题在动态实时优化 (DRTO) 级别以移动水平方式解决，以计算分配给较低级别​​分布式 MPC 子系统的设定点，其公式保持完整。案例研究结果表明，这些策略可以显着减少闭环集成调度和控制问题的求解时间，而不会严重影响工厂性能。我们证明，即使存在工厂模型不匹配的情况，所提出的集成调度和控制公式也可以成功地协调 MPC 子系统，以满足不同产品等级的市场需求。