1. Production scheduling and linear MPC: Complete integration via complementarity conditions.
- Author
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Simkoff, Jodie M. and Baldea, Michael
- Subjects
- *
PRODUCTION scheduling , *LINEAR complementarity problem , *PREDICTIVE control systems , *CHEMICAL process control , *CHEMICAL process industries , *COMPLEMENTARITY constraints (Mathematics) - Abstract
• We present a novel framework for completely integrated scheduling and model predictive control of chemical processes. • The controller behavior is represented fully and explicitly by including the MPC KKT conditions directly in the scheduling formulation. • Two case studies demonstrate that schedules obtained using knowledge of closed-loop dynamics lead to increased profit compared with "open-loop" scheduling approaches. Competitive global market conditions and the availability of real-time pricing data call for agile and flexible operations in the chemical process industries. As the operating paradigm shifts, process scheduling decisions may consider a shorter time scale, and interactions with the process control layer become significant. The integration of these two decision-making layers is an active area of research. In this work, we propose a novel framework for the integration of production scheduling and linear model predictive control. Our approach explicitly represents the closed-loop response of the system by embedding the KKT conditions of the controller in a nonlinear programming formulation of the optimal scheduling problem. We present two case studies which demonstrate that control-informed scheduling leads to superior realized performance compared with a hierarchical, sequential decision-making structure. [ABSTRACT FROM AUTHOR]
- Published
- 2019
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