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Process Optimization using High Throughput Automated Micro-Bioreactors in Chinese Hamster Ovary Cell Cultivation

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Online automatic tuning and control for fed-batch cultivation.

Zita I T A Soons¹, Gerrit van Straten, Leo A van der Pol

¹Systems and Control Group, Wageningen University, Wageningen, The Netherlands. zita.soons@wur.nl

Bioprocess and Biosystems Engineering

|December 25, 2007

Summary

This summary is machine-generated.

This study introduces automatic tuning for specific growth rate control in bioproduction. The novel methods enhance controller performance, ensuring stable fed-batch cultivation of Bordetella pertussis.

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Area of Science:

Biotechnology
Control Engineering
Bioprocess Engineering

Background:

Controller performance in biotechnological production often falls short of expectations.
Online automatic tuning offers a solution by dynamically adjusting control parameters.
Specific growth rate control is crucial for optimizing fed-batch cultivations.

Purpose of the Study:

To present and evaluate automatic tuning approaches for model reference specific growth rate control.
To improve the performance and robustness of controllers in fed-batch cultivation.
To demonstrate the effectiveness of these methods in a real-world bioprocess.

Main Methods:

Developed direct automatic tuning methods based on the error between observed and set-point specific growth rates.
Utilized adaptation rates combining error, squared error, and integral error.
Validated the controller and tuning methods through simulations and laboratory experiments with Bordetella pertussis.

Main Results:

Two automatic tuning methods demonstrated high efficiency.
The developed methods are robust against disturbances, parameter uncertainties, and initialization errors.
Application of the specific growth rate controller resulted in a stable bioprocess.

Conclusions:

Automatic tuning significantly enhances specific growth rate control in fed-batch cultivations.
The proposed methods are simple, robust, and effective for bioprocess optimization.
Successful application with Bordetella pertussis validates the approach for biotechnological production.