Skip to main content

Biomass Specific Growth Rate Utilization for Model-Based Process Control and Supervision

  • Conference paper

Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 103))

Abstract

Problems described in this paper are common for several types of processes widely used at industrial scale. However, this work is focused on fermentation as it is representative for wide range of processes where live cells are used. A model-based technique is proposed for process control and supervision. The aim of this paper is to discuss an approach where a indirect measurement of the specific growth rate is utilized for improvement of brewing fermentation process control and supervision. The indicated solution is pretty simple against the others examples from literature.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   259.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   329.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Arpornwichanop, A., Shomchoam, N.: Studies on optimal control approach in a fed-batch fermentation. Korean Journal of Chemical Engineering 24, 11–15 (2007)

    Article  Google Scholar 

  2. Baldyga, J., Henczka, M., Podgórska, W.: Obliczenia w inżynieri bioreaktorów. Oficyna Wydawnicza Politechniki Warszawskiej (1996) (in Polish)

    Google Scholar 

  3. Cimander, C., Mandenius, C.F.: Bioprocess control from a multivariate process trajectory. Bioprocess and Biosystems Engineering 26, 401–411 (2004)

    Article  Google Scholar 

  4. Costa, A.C., Dechechi, E.C., Silva, F.L.H., Maugeri, F., Maciel, R.: Simulated dynamics and control of an extractive alcoholic fermentation. Applied Biochemistry and Biotechnology 84–86, 577–593 (2000)

    Article  Google Scholar 

  5. Galvanauskas, V., Simutis, R., Lübbert, A.: Model-based design of biochemical processes: simulation studies and experimental tests. Biotechnology Letters 19, 1043–1047 (1997)

    Article  Google Scholar 

  6. Gee, D.A., Ramirez, W.F.: Optimal temperature control for batch beer fermentation. Biotechnology and Bioengineering 31, 224–234 (1988)

    Article  Google Scholar 

  7. Gupthar, A.S., Bhattacharya, S., Basu, T.K.: Evaluation of the maximum specific growth rate of a yeast indicating non-linear growth trends in batch culture. World Journal of Microbiology amd Biotechnology 16, 613–616 (2000)

    Article  Google Scholar 

  8. Levisauskas, D.: Inferential control of the specific growth rate in fed-batch cultivation processes. Biotechnology Letters 23, 1189–1195 (2001)

    Article  Google Scholar 

  9. Metzger, M.: Modelling, simulation and control of continuous processes. Jacek Skalmierski Computer Studio (2000)

    Google Scholar 

  10. Neeleman, R., Boxtel, A.: Estimation of specific growth rate from cell density measurements. Bioprocess and Biosystems Engineering 24, 179–185 (2001)

    Article  Google Scholar 

  11. Pakula, T.M., Salonen, K., Uusiatlo, J., Penttila, M.: The effect of specific growth rate on protein synthesis and secretion in the filamentous fungus trichoderma reesei. Microbiology 151, 135–143 (2005)

    Article  Google Scholar 

  12. Pirt, S.J.: The penicillin fermentation: a model for secondary metabolite production. In: Pirtferm papers, series A. Pirtferm Limited (1994)

    Google Scholar 

  13. Siliang, Z., Chu, J., Yingping, Z.: A multi-scale study of industrial fermentation processes and their optimization. Advances in Biochemical Engineering/Biotechnology 87, 97–150 (2004)

    Google Scholar 

  14. Sonnleitner, B.: Measurements, modeling and control, 3rd edn. ch. 10. Cambridge University Press, Cambridge (2006)

    Google Scholar 

  15. Stoyanov, S.: Robust multiple-input-multiple-output control of non-linear continuous fermentation processes. Bioprocess Engineering 23, 309–314 (2000)

    Article  Google Scholar 

  16. Titica, M., Landaud, S., Trelea, I.C., Latrille, E., Corrieu, G., Cheruy, A.: Modelling of higher alcohol and ester production kinetics based on co2 emission, with a view to beer flavour control by temperature and top pressure. Journal of the American Society of Brewing Chemists 54(4), 167–174 (2000)

    Google Scholar 

  17. Trelea, I.C., Latrille, L., Landaud, S., Corrieu, G.: Reliable estimation of the key variables and of their rates of change in alcoholic fermentation. Bioprocess and Biosystems Engineering 24, 227–237 (2001)

    Article  Google Scholar 

  18. Trelea, I.C., Titica, M., Corrieu, G.: Dynamic optimisation of the aroma production in brewing fermentation. Journal of Process Control 14, 1–16 (2004)

    Article  Google Scholar 

  19. Trelea, I.C., Titica, M., Landaud, S., Latrille, E., Corrieu, G., Cheruy, A.: Predictive modelling of brewing fermentation: from knowledge-based to black-box models. Mathematics and Computers in Simulation 56, 405–424 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  20. Uma Maheshwar Kiran, A., Jana, A.K.: Control of continuous fed-batch fermentation process using neural network based model predictive controller. Bioprocess and Biosystems Engineering 32, 801–808 (2009)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Strzępek, T. (2011). Biomass Specific Growth Rate Utilization for Model-Based Process Control and Supervision. In: Czachórski, T., Kozielski, S., Stańczyk, U. (eds) Man-Machine Interactions 2. Advances in Intelligent and Soft Computing, vol 103. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23169-8_18

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-23169-8_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23168-1

  • Online ISBN: 978-3-642-23169-8

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics