Dynamic Multi-Objective Optimization of Batch Chromatographic Separation Processes
(2015) 12th International Symposium on Process Systems Engineering and 25th European Symposium on Computer Aided Process Engineering 37. p.815-820- 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... (More)
- 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. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/7369888
- author
- Holmqvist, Anders LU ; Magnusson, Fredrik LU and Nilsson, Bernt LU
- organization
- publishing date
- 2015
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Batch chromatography, Dynamic multi-objective optimization, Collocation
- host publication
- Computer Aided Chemical Engineering
- editor
- Gernaey, Krist V. ; Huusom, Jakob K. and Gani, Rafiqul
- volume
- 37
- pages
- 6 pages
- publisher
- Elsevier
- conference name
- 12th International Symposium on Process Systems Engineering and 25th European Symposium on Computer Aided Process Engineering
- conference location
- Copenhagen, Denmark
- conference dates
- 2015-05-31 - 2015-06-04
- external identifiers
-
- wos:000366889500131
- scopus:84940514197
- ISSN
- 1570-7946
- ISBN
- 978-0-444-63429-0
- DOI
- 10.1016/B978-0-444-63578-5.50131-6
- project
- Numerical and Symbolic Algorithms for Dynamic Optimization
- LCCC
- language
- English
- LU publication?
- yes
- id
- cbbcbd00-fbc8-43c5-a4ce-20867d96c3d1 (old id 7369888)
- alternative location
- http://www.sciencedirect.com/science/article/pii/B9780444635785501316
- date added to LUP
- 2016-04-01 14:35:27
- date last changed
- 2023-10-30 02:10:37
@inproceedings{cbbcbd00-fbc8-43c5-a4ce-20867d96c3d1,
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.}},
author = {{Holmqvist, Anders and Magnusson, Fredrik and Nilsson, Bernt}},
booktitle = {{Computer Aided Chemical Engineering}},
editor = {{Gernaey, Krist V. and Huusom, Jakob K. and Gani, Rafiqul}},
isbn = {{978-0-444-63429-0}},
issn = {{1570-7946}},
keywords = {{Batch chromatography; Dynamic multi-objective optimization; Collocation}},
language = {{eng}},
pages = {{815--820}},
publisher = {{Elsevier}},
title = {{Dynamic Multi-Objective Optimization of Batch Chromatographic Separation Processes}},
url = {{https://lup.lub.lu.se/search/files/18788334/multi_obj_chrom.pdf}},
doi = {{10.1016/B978-0-444-63578-5.50131-6}},
volume = {{37}},
year = {{2015}},
}