High‐throughput screening of optimal process conditions using model predictive control-Reference-Cited by-同舟云学术

High‐throughput screening of optimal process conditions using model predictive control

Published:2022-10-08 Issue:12 Volume:119 Page:3584-3595
ISSN:0006-3592
Container-title:Biotechnology and Bioengineering
language:en
Short-container-title:Biotech & Bioengineering

Author:

Krausch Niels¹^ORCID,Kim Jong Woo¹^ORCID,Barz Tilman¹²^ORCID,Lucia Sergio³^ORCID,Groß Sebastian⁴^ORCID,Huber Matthias C.⁵,Schiller Stefan M.⁵^ORCID,Neubauer Peter¹^ORCID,Cruz Bournazou Mariano N.¹⁶^ORCID

Affiliation:

1. Chair of Bioprocess Engineering Technische Universität Berlin Berlin Germany

2. Center for Energy AIT Austrian Institute of Technology GmbH Vienna Austria

3. Process Automation Systems Technische Universität Dortmund Dortmund Germany

4. WEGA Informatik (Deutschland) GmbH Weil am Rein Germany

5. Institut für Pharmazeutische Technologie Goethe‐Universität Frankfurt Frankfurt Germany

6. DataHow AG Dübendorf Switzerland

Funder

Deutsche Forschungsgemeinschaft

Bundesministerium für Bildung und Forschung

Publisher

Wiley

Subject

Applied Microbiology and Biotechnology,Bioengineering,Biotechnology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/bit.28236

Reference47 articles.

1. A model‐based framework for parallel scale‐down fed‐batch cultivations in mini‐bioreactors for accelerated phenotyping

2. Modelling concentration gradients in fed-batch cultivations of E. coli - towards the flexible design of scale-down experiments

3. Optimal control of a nonlinear fed-batch fermentation process using model predictive approach

4. Substrate gradient formation in the large-scale bioreactor lowers cell yield and increases by-product formation

5. Nonlinear model predictive control of fed-batch fermentations using dynamic flux balance models

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