On-line estimation of biomass concentration using a neural network and information about metabolic state

Bioprocess and Biosystems Engineering

Volumn 27, Issue 1, 2004, Pages 9-15

  Vanek M ^a   Hrncirik P ^a   Vovsik J ^a   Nahlik J ^a  

^a INSTITUTE OF CHEMICAL TECHNOLOGY   (Czech Republic)

Author keywords

Baker's yeast; Biomass estimation; Metabolic state; Neural network; Software sensor

Indexed keywords

CONCENTRATION (PROCESS); CULTIVATION; METABOLISM; MICROORGANISMS; NEURAL NETWORKS; YEAST;

BAKER'S YEAST; BIOMASS CONCENTRATION; CASCADE CORRELATION; METABOLIC STATE (MS);

BIOMASS;

ARTICLE; ARTIFICIAL NEURAL NETWORK; BIOMASS; CORRELATION ANALYSIS; FUNGAL METABOLISM; ONLINE SYSTEM; PRIORITY JOURNAL; SACCHAROMYCES CEREVISIAE;

ALGORITHMS; BIOMASS; CELL PROLIFERATION; COMPUTER SIMULATION; ENERGY METABOLISM; INFORMATION STORAGE AND RETRIEVAL; MODELS, BIOLOGICAL; NEURAL NETWORKS (COMPUTER); ONLINE SYSTEMS; OXYGEN CONSUMPTION; SACCHAROMYCES CEREVISIAE;

BIOMASS; CONCENTRATION; CULTIVATION; METABOLISM; MICROORGANISMS; NEURAL NETWORKS; YEASTS;

EID: 12944274784     PISSN: 16157591     EISSN: None     Source Type: Journal    
DOI: 10.1007/s00449-004-0371-3     Document Type: Article

References (15)

1. Willis MJ, Montague GA, Di Massimo C, Tham MT, Morris AJ (1992) Artificial neural networks in process estimation and control. Automatica 28:1181-1187
2. Chen L, Zhang J, Morris AJ, Montague GA, Kent CA, Norton JP (1995) Combining neural networks with physical knowledge in modeling and state estimation of bioprocesses. In: Proc 3rd European Control Conf. Springer, Berlin Heidelberg New York, pp 2426-2431
3. Warnes MR, Glassey J, Montague GA, Kara B (1995) Comparing different modeling techniques for the Escherichia Coli fermentation process. In: Proc 6th IFAC Int Conf Computer Applications in Biotechnology. Pergamon, Oxford, UK, pp 142-147
4. Kurtanjek Ž (1994) Modeling and control by artificial neural networks in biotechnology. Comput Chem Eng 18:S627-631
5. Simutis R (1997) Application of hybrid modeling methods for biochemical process monitoring and optimization. In: Zimmermann HJ (ed) Proc 5th European Congr Intelligent Techniques and Soft Computing (EUFIT '97). Verlag Mainz, Aachen, Germany, pp 2154-2158
6. Ignova M, Montague GA, Ward AC, Glassey J, Kornfeld G, Thomas CR (1998) Hybrid modeling and optimization of industrial fed-batch fermentation process. In: Proc 7th IFAC Int Conf on Computer Applications in Biotechnology. Pergamon, Oxford, UK, pp 271-276
7. James SC, Legge RL, Budman H (2002) Comparative study of black-box and hybrid estimation methods in fed-batch fermentation. J Process Control 12:113-121
8. Simutis R, Havlik I, Lübbert A (1993) Fuzzy aided neural network for real time state estimation and process prediction in the alcohol formation step of production-scale beer brewing. J Biotechnol 27:203-215
9. Schubert J, Simutis R, Dors M, Havlik I, Lübbert A (1994) Bioprocess optimization and control: application of hybrid modelling. J Biotechnol 35:51-68
10. Leal RR, Butler P, Lane P, Payne PA (1997) Data fusion and artificial neural networks for biomass estimation. IEE P-Sci Meas Tech 144:69-72
11. Bachinger TH, Martensson P, Mandenius C-F (1998) Estimation of biomass and specific growth rate in a recombinant Escherichia coli batch cultivation process using a chemical multisensor array. J Biotechnol 60:55-66
12. Fahlman SE, Lebiere C (1991) The cascade correlation learning architecture. Carnegie Mellon University, Pittsburgh, PA
13. Hrnčiřík P, Náhlík J, Vovsík J (2002) The BIOGENES system for knowledge-based bioprocess control. Expert Syst Appl 23:145-153
14. Kristiansen B (1994) Integrated design of a fermentation plant. VCH, Weinheim, Germany
15. Baum EB, Haussler D (1989) What size net gives valid generalization? Neural Comput 1:151-160