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Related Experiment Videos

A predictive and feedback control algorithm maintains a constant glucose concentration in fed-batch fermentations.

G L Kleman1, J J Chalmers, G W Luli

  • 1Department of Microbiology, Ohio State University, Columbus 43210.

Applied and Environmental Microbiology
|April 1, 1991
PubMed
Summary

A new algorithm precisely controls glucose levels during Escherichia coli fermentation. This method uses predictive and feedback control for optimal nutrient feeding and high cell density growth.

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Area of Science:

  • Biotechnology
  • Biochemical Engineering
  • Microbial Fermentation

Background:

  • Fed-batch fermentation is crucial for high-density microbial cultures.
  • Precise control of nutrient feeding, especially glucose, is vital for optimizing fermentation performance.
  • Existing control methods may lack the precision needed for demanding bioprocesses.

Purpose of the Study:

  • To develop and evaluate a combined predictive and feedback control algorithm for fed-batch fermentation of Escherichia coli.
  • To maintain tight control over glucose concentration during microbial growth.
  • To achieve high cell densities through optimized nutrient feeding.

Main Methods:

  • Developed a combined predictive and feedback control algorithm.
  • Utilized on-line glucose concentration measurements.

Related Experiment Videos

  • Implemented a predictive algorithm based on linear regression of glucose demand.
  • Employed a proportional feedback controller for fine-tuning nutrient feed rates.

    • Main Results:

    • Successfully controlled glucose concentrations to within 0.49 +/- 0.04 g/liter.
    • Enabled growth of Escherichia coli to high cell densities.
    • Demonstrated effective "coarse" predictive control and precise feedback fine-tuning.

    Conclusions:

    • The combined control algorithm effectively manages glucose levels in fed-batch fermentations.
    • This approach is suitable for achieving high cell densities in Escherichia coli cultures.
    • Precise glucose control is a key factor in optimizing microbial bioprocesses.