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

YILMAZER HİTİT Z., Boyacioglu H., ÖZYURT B., ERTUNÇ S., HAPOĞLU H., AKAY B.

APPLIED BIOCHEMISTRY AND BIOTECHNOLOGY, cilt.172, sa.8, ss.3761-3775, 2014 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 172 Sayı: 8
  • Basım Tarihi: 2014
  • Doi Numarası: 10.1007/s12010-014-0794-5
  • Dergi Adı: APPLIED BIOCHEMISTRY AND BIOTECHNOLOGY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.3761-3775
  • Anahtar Kelimeler: Self-tuning generalized minimum variance control (STGMV), Bioreactor, Saccharomyces cerevisiae, Baker's yeast, System identification, Glucose concentration control, SACCHAROMYCES-CEREVISIAE, FERMENTATION PROCESS, CULTURE, OPTIMIZATION
  • Ankara Üniversitesi Adresli: Evet

Özet

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 (lambda), initial value of the covariance matrix (alpha), 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 lambda = 0.9, alpha = 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.