Computer Applications in Fermentation Technology: Modelling and Control of Biotechnological Processes pp 205-209 | Cite as
Identification of a Simulated Continuous Yeast Fermentation
Abstract
This work deals with multivariable adaptive identification of a simulated continuous yeast fermentation. The purpose of the identification is to obtain a model which can be used in a multivariable adaptive controller. A dynamic, structured, non-segregated model with eight state variables is used to simulate the process. A linear model (ARMAX-type) is identified by a Recursive Extended Least Squares method with a variable forgetting factor. Perturbations in two input variables are applied. Validation of the identified models is based on singular value analysis in the frequency domain.
Keywords
Dilution Rate Distillation Column Output Space Gain Curve Steady State DataPreview
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References
- Andersen, H, W.,1987:“MIMOFAD”, ver.0.5, sept.2,1987, user manual, Internal report, Instituttet for Kemiteknik, Technical University of Denmark. Google Scholar
- Andersen, H, W.,1988:“Advanced Control of Distillation Columns”, Ph.D. thesis, Instituttet for Kemiteknik, Technical University of Denmark.Google Scholar
- Goldschmidt, L, Hallager, L.& Jørgensen.SB.,1984:“Multivariable adaptive identification and control of a distributed chemical reactor”. Large Scale Systems,6, pp. 323–336. Google Scholar
- Lau, H., Alvarez, J.& Jensen, KF. (1985):“Synthesis of control structures by singular value analysis: Dynamic measures of sensitivity and interaction”. AlChE Journal,31,3, pp. 427–439. CrossRefGoogle Scholar
- Lievense, J.C. (1984):“An investigation of the aerobic, glucose-limited growth and dynamics of Saccharo-myces carevistae”, Ph.D thesis, Purdue University.Google Scholar
- Rolf, MJ.& Lim, HC. (1984):“Adaptive on-line optimization for continuous bioreactors”, Chemical Engineering Communications,29, pp. 229–255. Google Scholar