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Nonlinear Model Predictive Control of a CO 2 Post‐Combustion Absorption Unit
Author(s) -
Åkesson J.,
Laird C. D.,
Lavedan G.,
Prölß K.,
Tummescheit H.,
Velut S.,
Zhu Y.
Publication year - 2012
Publication title -
chemical engineering and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.403
H-Index - 81
eISSN - 1521-4125
pISSN - 0930-7516
DOI - 10.1002/ceat.201100480
Subject(s) - model predictive control , control theory (sociology) , combustion , nonlinear system , absorption (acoustics) , power (physics) , process (computing) , process engineering , nonlinear model , power station , computer science , control (management) , control engineering , engineering , chemistry , materials science , thermodynamics , physics , organic chemistry , quantum mechanics , artificial intelligence , composite material , electrical engineering , operating system
A dynamic model of a chemical CO 2 absorption process with aqueous monoethanolamine (MEA) is presented, validated against experimental data. Based on the validated model, a reduced‐order model is developed, suitable for an online optimization control strategy. The objective of the optimization is to enable fast adaptations to changes in operating conditions of the power plant, while minimizing the energy consumption in the operation of the CO 2 separation plant. The results indicate that model‐based online optimization is a feasible technology for control of CO 2 separation systems.