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Production scheduling in dynamic real-time optimization with closed-loop prediction
Journal of Process Control ( IF 4.2 ) Pub Date : 2020-05-01 , DOI: 10.1016/j.jprocont.2020.03.009
Jerome E.J. Remigio , Christopher L.E. Swartz

Abstract Process plants are operating in an increasingly dynamic environment, fueled largely by globalization and deregulation of energy markets, resulting in fluctuating market conditions and large variations in electricity prices. Such conditions pose challenges for traditional hierarchical plant decision-making systems, leading to efforts toward integration across the decision-making layers. This paper proposes a formulation for integration of production scheduling decisions within a dynamic real-time optimization (DRTO) framework. The DRTO formulation utilizes a closed-loop prediction of the plant response under the action of constrained model predictive control (MPC). The integrated scheduling and DRTO system communicates decisions to the underlying MPC system through time-varying set-point trajectories, thereby permitting the standard MPC implementation to be retained. The efficacy of the prosed system is illustrated through application to both single-input single-output (SISO) and multi-input multi-output (MIMO) case studies.

中文翻译:

具有闭环预测的动态实时优化中的生产调度

摘要 加工厂正在一个日益动态的环境中运行,这主要是由于能源市场的全球化和放松管制,导致市场条件波动和电价的巨大变化。这种情况对传统的分层工厂决策系统提出了挑战,导致跨决策层的整合努力。本文提出了一种在动态实时优化 (DRTO) 框架内集成生产调度决策的公式。DRTO 公式在约束模型预测控制 (MPC) 的作用下利用对设备响应的闭环预测。集成调度和 DRTO 系统通过时变设定点轨迹将决策传达给底层 MPC 系统,从而允许保留标准的 MPC 实现。通过对单输入单输出 (SISO) 和多输入多输出 (MIMO) 案例研究的应用,说明了所提出系统的功效。
更新日期:2020-05-01
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