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Fuzzy Control with Genetic Algorithm in a Batch Bioreactor

Applied Biochemistry and Biotechnology volume 171, pages 2201–2219 (2013)Cite this article

Abstract

In this study, the growth medium temperature in a batch bioreactor was controlled at the set point by using fuzzy model-based control method. Fuzzy control parameters which are membership functions and relation matrix were found using genetic algorithm. Heat input given from the immersed heater and the cooling water flow rate were selected as the manipulated variables in order to control the growth medium temperature in the bioreactor. Controller performance was tested in the face of different types of input variables. To eliminate the noise on the temperature measurements, first-order filter was used in the control algorithm. The achievement of the temperature control was analyzed in terms of both microorganism concentration which was reached at the end of the stationary phase and the performance criteria of Integral of the Absolute Error. It was concluded that the cooling flow rate was suitable as manipulated variable with regard to microorganism concentration. On the other hand, performance of the controller was satisfactory when the heat input given from the immersed heater was manipulated variable.

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Abbreviations

A T :

Heat transfer surface area, m2

C S :

Substrate concentration, g substrate /L

C X :

Microorganism (yeast) concentration, g cell /L

k d :

First-order death-rate constant

m C :

Cooling water flow rate, g/s

N :

Population size

OUR:

Oxygen uptake rate, g O2 /L.h

Q GR :

Generated reaction heat, J

p c :

Probability of crossover

p m :

Probability of mutation

t :

Time, h, s

T :

Bioreactor temperature, °C

Tc:

Mean temperature of cooling water, °C

Tci :

Inlet temperature of cooling water, °C

Tco :

Outlet temperature of cooling water, °C

U :

Overall heat transfer coefficient, J/m2 s °C

V C :

Volume of cooling water, cm3

V L :

Volume of growth medium, cm3

Y X/S :

Substrate yield coefficient, g cell/g substrate

Y X/O2 :

Oxygen yield coefficient, g cell/g O2

1/Y H :

Metabolic heat evolved per gram of cell mass produced, J/g cell

μ :

Specific growth rate, 1/h

ρ :

Growth medium density, g/cm3

ρ C :

Cooling water density, g/cm3

ΔH S :

Heat of combustion of the substrate, J/mol substrate

ΔH C :

Heat of combustion of cells, J/g cell

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Affiliations

  1. Faculty of Engineering, Department of Chemical Engineering, Ankara University, Tandogan, 06100, Ankara, Turkey

    Suna Ahioğlu, Suna Ertunç & Hale Hapoğlu

  2. Faculty of Engineering, Department of Chemical Engineering, Gazi University, Maltepe, 06570, Ankara, Turkey

    Ayla Altinten & Sebahat Erdoğan

Authors
  1. Suna Ahioğlu
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  2. Ayla Altinten
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  3. Suna Ertunç
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  4. Sebahat Erdoğan
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  5. Hale Hapoğlu
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Correspondence to Ayla Altinten.

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Ahioğlu, S., Altinten, A., Ertunç, S. et al. Fuzzy Control with Genetic Algorithm in a Batch Bioreactor. Appl Biochem Biotechnol 171, 2201–2219 (2013). https://doi.org/10.1007/s12010-013-0488-4

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  • DOI: https://doi.org/10.1007/s12010-013-0488-4

Keywords

  • Fuzzy control
  • Bioreactor
  • S. cerevisiae
  • Genetic algorithm (GA)
  • Temperature control