Bioprocess and Biosystems Engineering

, Volume 26, Issue 5, pp 331–340 | Cite as

Computer control of pH and DO in a laboratory fermenter using a neural network technique

  • A. Mészáros
  • A. Andrášik
  • P. Mizsey
  • Z. Fonyó
  • V. Illeová
Original Paper


In this contribution, the advantages of the artificial neural network approach to the identification and control of a laboratory-scale biochemical reactor are demonstrated. It is very important to be able to maintain the levels of two process variables, pH and dissolved oxygen (DO) concentration, over the course of fermentation in biosystems control. A PC-supported, fully automated, multi-task control system has been designed and built by the authors. Forward and inverse neural process models are used to identify and control both the pH and the DO concentration in a fermenter containing a Saccharomyces cerevisiae based-culture. The models are trained off-line, using a modified back-propagation algorithm based on conjugate gradients. The inverse neural controller is augmented by a new adaptive term that results in a system with robust performance. Experimental results have confirmed that the regulatory and tracking performances of the control system proposed are good.


Laboratory fermenter Control system Neural networks 



The authors are pleased to acknowledge the financial support of the Scientific Grant Agency of the Slovak Republic under grants No. 1/0135/03 and 1/1046/04. Since part of the work has been completed under financial support of the 2003 Szent-Györgyi Fellowship, authors wish also to thank the Hungarian Ministry of Education for cooperation.


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Copyright information

© Springer-Verlag 2004

Authors and Affiliations

  • A. Mészáros
    • 1
  • A. Andrášik
    • 1
  • P. Mizsey
    • 2
  • Z. Fonyó
    • 2
  • V. Illeová
    • 1
  1. 1.Faculty of Chemical and Food TechnologySlovak University of TechnologyBratislavaSlovak Republic
  2. 2.Faculty of Chemical EngineeringBudapest University of Technology and EconomicsBudapestHungary

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