An economic model predictive control approach to integrated production management and process operation |
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| Authors: | Anas Alanqar Helen Durand Fahad Albalawi Panagiotis D. Christofides |
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| Affiliation: | 1. Dept. of Chemical and Biomolecular Engineering, University of California, Los Angeles, CA;2. Dept. of Electrical Engineering, University of California, Los Angeles, CA |
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| Abstract: | Managing production schedules and tracking time‐varying demand of certain products while optimizing process economics are subjects of central importance in industrial applications. We investigate the use of economic model predictive control (EMPC) in tracking a production schedule. Specifically, given that only a small subset of the total process state vector is typically required to track certain scheduled values, we design a novel EMPC scheme, through proper construction of the objective function and constraints, that forces specific process states to meet the production schedule and varies the rest of the process states in a way that optimizes process economic performance. Conditions under which feasibility and closed‐loop stability of a nonlinear process under such an EMPC for schedule management can be guaranteed are developed. The proposed EMPC scheme is demonstrated through a chemical process example in which the product concentration is requested to follow a certain production schedule. © 2016 American Institute of Chemical Engineers AIChE J, 63: 1892–1906, 2017 |
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| Keywords: | nonlinear systems scheduling production management economic model predictive control process control process optimization process economics nonlinear processes |
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