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Adaptive pole placement control algorithm for DO-control in beta-lactamase production.

I G Sargantanis¹, M N Karim

¹Department of Chemical and Bioresource Engineering, Colorado State University, Fort Collins, Colorado 80523, USA.

Biotechnology and Bioengineering

|April 1, 1999

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Controlling dissolved oxygen (DO) in aerobic fermentations is challenging. This study developed an adaptive control algorithm to improve DO regulation and enhance beta-lactamase production by Bacillus subtilis.

Area of Science:

Biotechnology
Biochemical Engineering
Process Control

Background:

Dissolved oxygen (DO) is critical for aerobic fermentation, impacting cell growth and product formation.
Controlling DO in batch fermentations is complex due to dynamic conditions, time delays, and sensor limitations.
Accurate modeling of biological activity is essential for effective DO control and pattern tracking.

Purpose of the Study:

To develop and evaluate an adaptive control strategy for dissolved oxygen in aerobic fermentations.
To investigate the impact of DO levels on beta-lactamase production by Bacillus subtilis.
To improve the stability and productivity of beta-lactamase under oxygen-limited conditions.

Main Methods:

Implemented an adaptive pole placement algorithm with time-delay compensation for DO control.

Related Experiment Videos

Utilized system identification with recursively estimated autoregressive models with exogenous inputs (ARX).

Employed supervision and coordination techniques to enhance control performance, manipulating O2 flow rate.

Main Results:

The adaptive control algorithm demonstrated improved DO regulation in batch fermentations.
Model prediction accuracy and time delay compensation significantly affected control performance.
Oxygen-limited conditions and low DO levels enhanced beta-lactamase stability and productivity in Bacillus subtilis.

Conclusions:

Adaptive control strategies are effective for managing dissolved oxygen in challenging fermentation processes.
Optimizing DO levels can significantly enhance the yield and stability of bioproducts like beta-lactamase.
This approach offers a pathway for improved bioprocess control and product optimization.