Reduced order modeling of high purity distillation columns for nonlinear model predictive control
S Khowinij, S Bian, MA Henson… - Proceedings of the …, 2004 - ieeexplore.ieee.org
S Khowinij, S Bian, MA Henson, P Belanger, L Megan
Proceedings of the 2004 American Control Conference, 2004•ieeexplore.ieee.orgFundamental dynamic models of distillation columns are not well suited for incorporation
into nonlinear model predictive control schemes due to their high state dimension. We
investigate two reduced order nonlinear modeling techniques for high purity distillation
columns. Compartmental and nonlinear wave models developed for a nitrogen purification
column are compared to a rigorous dynamic simulator to assess the relative tradeoffs
between prediction accuracy and computational complexity. The utility of each reduced …
into nonlinear model predictive control schemes due to their high state dimension. We
investigate two reduced order nonlinear modeling techniques for high purity distillation
columns. Compartmental and nonlinear wave models developed for a nitrogen purification
column are compared to a rigorous dynamic simulator to assess the relative tradeoffs
between prediction accuracy and computational complexity. The utility of each reduced …
Fundamental dynamic models of distillation columns are not well suited for incorporation into nonlinear model predictive control schemes due to their high state dimension. We investigate two reduced order nonlinear modeling techniques for high purity distillation columns. Compartmental and nonlinear wave models developed for a nitrogen purification column are compared to a rigorous dynamic simulator to assess the relative tradeoffs between prediction accuracy and computational complexity. The utility of each reduced order modeling technique for nonlinear model predictive control of high purity distillation columns is discussed.
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