Adaptive optimal operation of a parallel robotic liquid handling station

被引：19

作者：

Barz, Tilman ^{[1
]}

Sommer, Andreas ^{[2
]}

Wilms, Terrance ^{[3
]}

Neubauer, Peter ^{[3
]}

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

机构：

[1] AIT Austrian Inst Technol GmbH, Ctr Energy, Vienna, Austria

[2] Heidelberg Univ, Interdisciplinary Ctr Sci Comp IWR, Heidelberg, Germany

[3] Tech Univ Berlin, Chair Bioproc Engn, Inst Biotechnol, Berlin, Germany

来源：

IFAC PAPERSONLINE | 2018年 / 51卷 / 02期

关键词：

Parallel robotic liquid handling station; E. coli kinetic model; Optimal experimental design for model calibration; Adaptive input design; Identifiability and ill-conditioning analysis; DESIGN; AUTOMATION;

D O I：

10.1016/j.ifacol.2018.04.006

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Results are presented from the optimal operation of a fully automated robotic liquid handling station where parallel experiments are performed for calibrating a kinetic fermentation model. To increase the robustness against uncertainties and/or wrong assumptions about the parameter values, an iterative calibration and experiment design approach is adopted. Its implementation yields a stepwise reduction of parameter uncertainties together with an adaptive redesign of reactor feeding strategies whenever new measurement information is available. The case study considers the adaptive optimal design of 4 parallel fed-batch strategies implemented in 8 mini-bioreactors. Details are given on the size and complexity of the problem and the challenges related to calibration of over-parameterized models and scarce and non-informative measurement data. It is shown how methods for parameter identifiability analysis and numerical regularization can be used for monitoring the progress of the experimental campaigns in terms of generated information regarding parameters and selection of the best fitting parameter subset. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

引用

页码：765 / 770

页数：6

共 12 条

[1] Kinetic models in industrial biotechnology - Improving cell factory performance [J].