Real-time adaptive input design for the determination of competitive adsorption isotherms in liquid chromatography

被引：17

作者：

Barz, Tilman ^{[1
]}

Lopez, Diana C. C. ^{[2
]}

Bournazou, M. Nicolas Cruz ^{[3
]}

Koerkel, Stefan ^{[4
]}

Walter, Sebastian F. ^{[5
]}

机构：

[1] AIT Austrian Inst Technol GmbH, Giefinggasse 2, A-1210 Vienna, Austria

[2] Tech Univ Berlin, Chair Proc Dynam & Operat, Str 17 Juni 135, D-10623 Berlin, Germany

[3] Tech Univ Berlin, Inst Biotechnol, Dept Bioproc Engn, Ackerstr 71-76, D-13355 Berlin, Germany

[4] Univ Mannheim, Sch Business Informat & Math, B6,26, D-68131 Mannheim, Germany

[5] Heidelberg Univ, Interdisciplinary Ctr Sci Comp, Neuenheimer Feld 368, D-69120 Heidelberg, Germany

来源：

COMPUTERS & CHEMICAL ENGINEERING | 2016年 / 94卷

关键词：

Adaptive input design; Regularization techniques; Model based optimal experimental re-design; Parameter estimation; PARAMETER-ESTIMATION; RIDGE-REGRESSION; IDENTIFICATION; OPTIMIZATION; SYSTEMS; TRAJECTORIES; EXCITATION; SELECTION; REDESIGN;

D O I：

10.1016/j.compchemeng.2016.07.009

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

The adaptive input design (also called online redesign of experiments) for parameter estimation is very effective for the compensation of uncertainties in nonlinear processes. Moreover, it enables substantial savings in experimental effort and greater reliability in modeling. We present theoretical details and experimental results from the real-time adaptive optimal input design for parameter estimation. The case study considers separation of three benzoate by reverse phase liquid chromatography. Following a receding horizon scheme, adaptive D-optimal input designs are generated for a precise determination of competitive adsorption isotherm parameters. Moreover, numerical techniques for the regularization of arising ill-posed problems, e.g. due to scarce measurements, lack of prior information about parameters, low sensitivities and parameter correlations are discussed. The estimated parameter values are successfully validated by Frontal Analysis and the benefits of optimal input designs are highlighted when compared to various standard/heuristic input designs in terms of parameter accuracy and precision. (C) 2016 Elsevier Ltd. All rights reserved.

引用

页码：104 / 116

页数：13

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