Skip to main content
SpringerLink
Log in

Self-Tuning GMV Control of Glucose Concentration in Fed-Batch Baker’s Yeast Production

  • Published:
Applied Biochemistry and Biotechnology Aims and scope Submit manuscript

Abstract

A detailed system identification procedure and self-tuning generalized minimum variance (STGMV) control of glucose concentration during the aerobic fed-batch yeast growth were realized. In order to determine the best values of the forgetting factor (λ), initial value of the covariance matrix (α), and order of the Auto-Regressive Moving Average with eXogenous (ARMAX) model (n a, n b), transient response data obtained from the real process wereutilized. Glucose flow rate was adjusted according to the STGMV control algorithm coded in Visual Basic in an online computer connected to the system. Conventional PID algorithm was also implemented for the control of the glucose concentration in aerobic fed-batch yeast cultivation. Controller performances were examined by evaluating the integrals of squared errors (ISEs) at constant and random set point profiles. Also, batch cultivation was performed, and microorganism concentration at the end of the batch run was compared with the fed-batch cultivation case. From the system identification step, the best parameter estimation was accomplished with the values λ = 0.9, α = 1,000 and n a = 3, n b = 2. Theoretical control studies show that the STGMV control system was successful at both constant and random glucose concentration set profiles. In addition, random effects given to the set point, STGMV control algorithm were performed successfully in experimental study.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14

Similar content being viewed by others

References

  1. Akesson, M., Hagander, P., & Axelsson, J. P. (2001). Probing control of fed-batch cultivations: analysis and tuning. Control Engineering Practice, 9, 709–723.

    Article  Google Scholar 

  2. Honda, H., Lenas, P., Watanable, H., Kitade, T., & Kobayashi, T. (1998). Human antithrombin III variant production from recombinant BHK cells in a fed-batch culture with on-line control of glucose and glutamine concentrations. Journal of Fermentation and Bioengineering, 85(5), 532–535.

    Article  CAS  Google Scholar 

  3. Arrizon, J., & Gschaedler, A. (2002). Increasing fermentation efficiency at high sugar concentrations by supplementing an additional source of nitrogen during the exponential phase of tequila fermentation process. Canadian Journal of Microbiology, 48, 965–970.

    Article  CAS  Google Scholar 

  4. Ronen, M., Shabtai, Y., & Guterman, H. (2002). Optimization of feeding profile for a fed-batch bioreactor by an evaluationary algorithm. Journal of Biotechnology, 97, 253–263.

    Article  CAS  Google Scholar 

  5. Ringbom, K., Rothberg, A., & Saxen, R. (1996). Model-based automation of baker’s yeast production. Journal of Biotechnology, 51, 73–82.

    Article  CAS  Google Scholar 

  6. Henes, B., & Sonnleitner, B. (2007). Controlled fed-batch by tracking the maximal culture capacity. Journal of Biotechnology, 132, 118–126.

    Article  CAS  Google Scholar 

  7. Klockow, C., Hüll, D., & Hitzmann, B. (2008). Model based substrate set point control of yeast cultivation processes based on FIA measurements. Analytica Chimica Acta, 623, 30–37.

    Article  CAS  Google Scholar 

  8. Yüzgeç, U., Türker, M., & Hocalar, A. (2009). On-line evolutionary optimization of an industrial fed-batch yeast fermentation process. ISA Transactions, 79–92.

  9. Shuler, M. L., & Kargi, F. (2002). Biyoproses Engineering Basic Concepts (2nd ed.). New Jersey: Prentice Hall.

    Google Scholar 

  10. Clarke, D. W., & Gawthrop, P. J. (1975). Self Tuning Controller. Proc. IEE, 122(9), 929–934.

    Google Scholar 

  11. Williams, D., Yousefpour, P., & Wellington, E. M. H. (1986). On-line adaptive control of a fed-batch fermentation of Saccharomyces cerevisiae. Biotechnology and Bioengineering, 28, 631–645.

    Article  CAS  Google Scholar 

  12. Zigova, J. (2000). Effect of RQ and pressed conditions on biomass galactocyl transferase production during fed-batch culture of S. Cerevisiae BT150. Journal of Biotechnology, 80, 55–62.

    Article  CAS  Google Scholar 

  13. Hisbullah, Hussain, M. A. & Ramachandran, K. B. (2003) Design of a fuzzy logic controller for regulating substrate feed to fed-batch fermentation. Institution of Chemical Engineers Trans IChemE, Vol 1, Part C.

  14. Karakuzu, C., Çakır, B., Öztürk, S., & Türker M. (2002) Yarı kesikli ekmek mayası fermantasyonunda bulanık mantık tabanlı hammadde besleme kontrolü, ELECO’2002 Elektrik-Elektronik-Bilgisayar Mühendisliği Sempozyumu Bildiriler Kitabı Elektronik Cildi, s. 305-309, 18–22 Aralık 2002, TÜBİTAK/Bursa.

  15. Peroni, C. V., Kaisare, N. S., & Lee, J. H. (2005) Optimal control of a fed-batch bioreactor using simulation-based approximate dynamic programming. Transactions on Control Systems Technology, Vol. 13, No. 5.

  16. Zhang, J. (2005). A neural network-based strategy for the integrated batch-to-batch control and within-batch control of batch processes. Transactions of the Institute of Measurement and Control, 27(5), 391–410.

    Article  Google Scholar 

  17. Hocalar, A., & Türker, M. (2010). Model based control of minimal overflow metabolite in technical scale fed-batch yeast fermentation. Biochemical Engineering Journal, 54, 64–71.

    Article  Google Scholar 

  18. Aström, K. J., & Wittenmark, B. (1973). On self-tuning regulators. Automatica, 9, 185–199.

    Article  Google Scholar 

  19. Wellstead, P. E., & Zarrop, M. B. (1991). Self-tuning system control and signal processing. Great Britain: John Wiley and Sons.

    Google Scholar 

Download references

Author information

Authors and Affiliations

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

    Zeynep Yilmazer Hitit, Havva Boyacioglu, Baran Ozyurt, Suna Ertunc, Hale Hapoglu & Bulent Akay

Authors
  1. Zeynep Yilmazer Hitit
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Havva Boyacioglu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Baran Ozyurt
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Suna Ertunc
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Hale Hapoglu
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Bulent Akay
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Zeynep Yilmazer Hitit.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Hitit, Z.Y., Boyacioglu, H., Ozyurt, B. et al. Self-Tuning GMV Control of Glucose Concentration in Fed-Batch Baker’s Yeast Production. Appl Biochem Biotechnol 172, 3761–3775 (2014). https://doi.org/10.1007/s12010-014-0794-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12010-014-0794-5

Keywords

Search

Navigation