Dynamic Multi-Objective Optimization of Batch Chromatographic Separation Processes

This contribution presents a novel offline dynamic multi-objective optimization framework for high-pressure liquid chromatographic (HPLC) processes in batch elution mode. The framework allows for optimization of general elution trajectories parametrized with piecewise constant control signals. It is...

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Published inComputer Aided Chemical Engineering Vol. 37; pp. 815 - 820
Main Authors Holmqvist, A., Magnusson, F., Nilsson, B.
Format Book Chapter
LanguageEnglish
Published 2015
Subjects
Online AccessGet full text
ISBN9780444634290
0444634290
ISSN1570-7946
2543-1331
DOI10.1016/B978-0-444-63578-5.50131-6

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Abstract This contribution presents a novel offline dynamic multi-objective optimization framework for high-pressure liquid chromatographic (HPLC) processes in batch elution mode. The framework allows for optimization of general elution trajectories parametrized with piecewise constant control signals. It is based on a simultaneous method where both the control and state variables are fully discretized in the temporal domain, using orthogonal collocations on finite elements, and the state variables are discretized in the spatial domain, using a finite volume weighted essentially non-oscillatory (WENO) scheme. The resulting finite dimensional nonlinear program (NLP) is solved using a primal-dual interior point method and automatic differentiation techniques. The advantages of this open-loop optimal control methodology are highlighted through the solution of a challenging ternary complex mixture separation problem for a hydrophobic interaction chromatography (HIC) system. For a bi-objective optimization of the target component productivity and yield, subject to a purity constraint, the set of Pareto solutions generated with general elution trajectories showed considerable improvement in the productivity objective when compared to the Pareto set obtained using conventional linear elution trajectories.
AbstractList This contribution presents a novel offline dynamic multi-objective optimization framework for high-pressure liquid chromatographic (HPLC) processes in batch elution mode. The framework allows for optimization of general elution trajectories parametrized with piecewise constant control signals. It is based on a simultaneous method where both the control and state variables are fully discretized in the temporal domain, using orthogonal collocations on finite elements, and the state variables are discretized in the spatial domain, using a finite volume weighted essentially non-oscillatory (WENO) scheme. The resulting finite dimensional nonlinear program (NLP) is solved using a primal-dual interior point method and automatic differentiation techniques. The advantages of this open-loop optimal control methodology are highlighted through the solution of a challenging ternary complex mixture separation problem for a hydrophobic interaction chromatography (HIC) system. For a bi-objective optimization of the target component productivity and yield, subject to a purity constraint, the set of Pareto solutions generated with general elution trajectories showed considerable improvement in the productivity objective when compared to the Pareto set obtained using conventional linear elution trajectories.
Author Nilsson, B.
Holmqvist, A.
Magnusson, F.
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Keywords Dynamic multi-objective optimization
Collocation
Batch chromatography
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Magnusson, Akesson (bb0045) 2012
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StartPage 815
SubjectTerms Batch chromatography
Chemical Engineering
Collocation
Control Engineering
Dynamic multi-objective optimization
Electrical Engineering, Electronic Engineering, Information Engineering
Elektroteknik och elektronik
Engineering and Technology
Kemiteknik
Reglerteknik
Teknik
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Title Dynamic Multi-Objective Optimization of Batch Chromatographic Separation Processes
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