Online estimation using dynamic flux balance model and multiparametric programming

被引：1
|
作者：
Shen, Xin [1 ]
Budman, Hector [1 ]
机构：
[1] Univ Waterloo, Dept Chem Engn, 200 Univ Ave W, Waterloo, ON N2L 3G1, Canada
来源：
COMPUTERS & CHEMICAL ENGINEERING | 2022年 / 164卷
基金：
加拿大自然科学与工程研究理事会;
关键词：
Set membership estimation; Weighted primal-dual method; Multiparametric nonlinear programming; Dynamic flux balance models; Multiple solutions; SOFT SENSOR;
D O I：
10.1016/j.compchemeng.2022.107872
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
An approach is proposed for online estimation of bounds on metabolite's concentrations based on limited measurements and Dynamic Flux Balance Models (DFBM) which use linear programming (LP) to model the evolution of metabolites with time. A Weighted primal-dual method to address the multiplicity of solutions of DFBMs is combined with multiparametric nonlinear programming (mpNLP) for set membership estimation. The set membership estimation (SME) approach is used to propagate the uncertainty onto metabolites' concentrations over time. By only measuring biomass concentration and culture volume, bounds of metabolites' concentrations can be estimated online by SME during the fermentation. The proposed algorithm is applied to batch and fed-batch fermentation of E. coli. (C) 2022 Elsevier Ltd. All rights reserved.
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页数：15
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