Discrete system identification and self-tuning control of dissolved oxygen concentration in a stirred reactor

Bulent Akay; Suna Ertunc; Havva Boyacioglu; Hale Hapoglu; Mustafa Alpbaz

Korean Journal of Chemical Engineering, Vol.28, No.3, 837-847, March, 2011

DOI10.1007/s11814-010-0450-x Export Citation

Discrete system identification and self-tuning control of dissolved oxygen concentration in a stirred reactor

Bulent Akay, Suna Ertunc^†, Havva Boyacioglu, Hale Hapoglu, and Mustafa Alpbaz

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

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This work presents the applications of discrete-time system identification and generalized minimum variance (GMV) control of dissolved oxygen (DO) level in a batch bioreactor in which Saccharomyces cerevisiae is produced at aerobic condition. Air flow rate and mixing rate were varied to determine the maximum local liquid phase volumetric mass transfer coefficient (KLa). Maximum KLa value was determined at a mixing rate of 600 rpm and air flow rate of 3.4 Lmin.1. For control purpose, manipulated variable was selected as air flow rate due to its effectiveness on the KLa. To examine the dynamic behavior of the bioreactor, various input signals were utilized as a forcing function and three different model orders were tested. A second0order controlled auto regressive moving average (CARMA) model was used as the process model in the control algorithm and in the system identification step. It is concluded that the ternary input is more suitable than the other input types used in this work for system identification. Recursive least squares method (RLS) was used to determine the model parameters. GMV control results were compared with the traditional PID control results by using performance criteria of IAE and ITAE for different types of DO set point trajectories. DO concentration in the batch bioreactor was controlled more successfully with an adaptive controller structure of GMV than the PID controller with fixed parameters.

Keywords:Dissolved Oxygen (DO);Generalised Minimum Variance (GMV);Controlled Auto Regressive Moving Average (CARMA);Bioreactor Control;Discrete System Identification

[References]

Astrom KJ, Wittenmark B, Automatica., 9, 185 (1973)
Clarke DW, Gawthrop PJ, Proc. IEE., 26(6), 633 (1979)
Omstead DR, Computer control of fermentation processes., CRC Press, Florida (1990)
Shuler L, Karg F, Bioprocess engineering basic concepts., Prentice Hall, New Jersey (1992)
Sales KR, Billings SA, Int. J. Control., 51, 753 (1990)
Svonoros S, Stephanopoulos G, Aris R, Int. J. Control., 34, 651 (1981)
Goodwin GC, McInnis B, Long RS, Optimal Control Applications and Methods., 3, 443 (1982)
Goodwin GC, Sin KS, Adaptive filtering prediction and control., Prentice-Hall, New Jersey (1984)
Omstead DR, Computer control of fermentation processes., CRC Press, Florida (1990)
Clarke TA, Hesketh T, Seddon T, Biotechnol. Bioeng., 17, 1507 (1985)
Sargantanis IG, Karim MN, Biotechnol. Bioeng., 60(1), 1 (1998)
Lee SC, Hwang YB, Chang HN, Chang YK, Biotechnol. Bioeng., 37, 597 (1991)
Suzuki T, Yamane T, Shimizu S, J. Ferm. Technol., 64(4), 317 (1986)
Williams D, Yousefpour P, E. M. H., Biotechnol. Bioeng., 28, 631 (1986)
Soderstrom T, Stoica P, System identification., Prentice Hall Ltd., New York (1989)
Wellstead PE, Zarrop MB, Self-tuning systems-control and signal processing., John Wiley & Sons, New York (1991)
Clarke DW, Gawthrop PJ, Proc. IEEE., 122(9), 929 (1975)
Karagoz AR, Hapoglu H, Alpbaz M, Chem. Eng. Process., 39(3), 253 (2000)
Ertunc S, Akay B, Bursali N, Hapoglu H, Alpbaz M, Food Bioprod. Process., 81, 327 (2003)
Ertunc S, Akay B, Boyacioglu H, Hapoglu H, Food Bioprod. Process., 87, 46 (2009)
Mohtadi C, Industrial Digital Control Systems “Chapter 7. Adaptive Control”: Warwick K and Rees D (Eds.), IEE Control Engineering Series 37, Institution of Engineering and Technology, London (1988)
Stephanopoulos G, Chemical process control., Prentice Hall, New Jersey (1984)

[Referenced By]

[1] Astrom KJ, Wittenmark B, Automatica., 9, 185 (1973)

[2] Clarke DW, Gawthrop PJ, Proc. IEE., 26(6), 633 (1979)

[3] Omstead DR, Computer control of fermentation processes., CRC Press, Florida (1990)

[4] Shuler L, Karg F, Bioprocess engineering basic concepts., Prentice Hall, New Jersey (1992)

[5] Sales KR, Billings SA, Int. J. Control., 51, 753 (1990)

[6] Svonoros S, Stephanopoulos G, Aris R, Int. J. Control., 34, 651 (1981)

[7] Goodwin GC, McInnis B, Long RS, Optimal Control Applications and Methods., 3, 443 (1982)

[8] Goodwin GC, Sin KS, Adaptive filtering prediction and control., Prentice-Hall, New Jersey (1984)

[9] Omstead DR, Computer control of fermentation processes., CRC Press, Florida (1990)

[10] Clarke TA, Hesketh T, Seddon T, Biotechnol. Bioeng., 17, 1507 (1985)

[11] Sargantanis IG, Karim MN, Biotechnol. Bioeng., 60(1), 1 (1998)

[12] Lee SC, Hwang YB, Chang HN, Chang YK, Biotechnol. Bioeng., 37, 597 (1991)

[13] Suzuki T, Yamane T, Shimizu S, J. Ferm. Technol., 64(4), 317 (1986)

[14] Williams D, Yousefpour P, E. M. H., Biotechnol. Bioeng., 28, 631 (1986)

[15] Soderstrom T, Stoica P, System identification., Prentice Hall Ltd., New York (1989)

[16] Wellstead PE, Zarrop MB, Self-tuning systems-control and signal processing., John Wiley & Sons, New York (1991)

[17] Clarke DW, Gawthrop PJ, Proc. IEEE., 122(9), 929 (1975)

[18] Karagoz AR, Hapoglu H, Alpbaz M, Chem. Eng. Process., 39(3), 253 (2000)

[19] Ertunc S, Akay B, Bursali N, Hapoglu H, Alpbaz M, Food Bioprod. Process., 81, 327 (2003)

[20] Ertunc S, Akay B, Boyacioglu H, Hapoglu H, Food Bioprod. Process., 87, 46 (2009)

[21] Mohtadi C, Industrial Digital Control Systems “Chapter 7. Adaptive Control”: Warwick K and Rees D (Eds.), IEE Control Engineering Series 37, Institution of Engineering and Technology, London (1988)

[22] Stephanopoulos G, Chemical process control., Prentice Hall, New Jersey (1984)