Abstract
This paper describes an application of feedforward neural networks for inverse plant control of a process with highly non-linear characteristics. A biochemical process was considered where the microorganism, Saccharomyces cerevisiae, a yeast, grows in a chemostat on a glucose substrate and produces ethanol as a product of primary energy metabolism. In this process, which is of immense interest to industries worldwide, three state variables were considered: microbial, substrate and product concentrations. The last one is the controlled variable, and the dilution rate is the manipulated variable. In the study, the quality of the control is analyzed for the case where all states are assumed to be measurable and the case where only the product concentration is available.
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References
Bavarian, B., “Introduction to Neural Network for Intelligent Control”, IEEE Control Systems Magazine, April 1988.
Ydstie, B. E., “Forecasting and control using adaptive connectionist networks”, Comput. chem. Engng. 14 (1990) p. 583–599.
Bhat N. and McAvoy, T. J., “Use of neural nets for dynamic modeling and control of chemical process systems” Comput. chem. Engng. 14 (1990) p. 573–582.
Antsaklis, P. J., “Neural networks in control systems”, IEEE Control Systems Magazine (April 1990) p. 3-5.
Ungar, L.H., B.A. Powell and S.N. Kamens, “Adaptive networks for fault diagnosis and process control”, Comput. chem. Engng. 14 (1990) p. 561–572.
Miller, W.T., R.S. Sutton and P.J. Werbos, “Neural networks for control”, MIT Press, Cambridge, USA, 1990.
Bulsari, A.B. and H. Saxén, “System identification of a biochemical process using feed-forward neural networks”, Neurocomputing 3 (1991) p. 125-133.
Elmqvist, H. et al., “Simnon user’s guide for MS-DOS computers, Version 3”, SSPA Systems, Göteborg, Sweden, 1990.
Bulsari, A.B. and H. Saxén, “Application of neural networks for filtering”, to be presented at International Conference on Neural Networks and Genetic Algorithms (ANNGA’ 93), Innsbruck, Austria, April 1993.
Bulsari, A.B. and H. Saxén, “System identification using the symmetric logarithmoid as an activation function in a feed-forward neural network”, Neural network world 1 (1991) p. 221–224.
Marquardt, D. W., “An algorithm for leastsquares estimation of nonlinear parameters”, J. SIAM 11 (1963) p. 431–441.
A. Bulsari, B. Saxén and H. Saxén, “Programs for feedforward neural networks using the Levenberg-Marquardt method: Documentation and user’s manual” Report 90–2, Heat Eng. Lab, Åbo Akademi, Finland, October 1990.
Bulsari, A. and H. Saxén, “Estimation of a disturbance variable using feed-forward neural networks”. Proceedings of the 11th IASTED International Conference on Modelling, Identification and Control (MIC’92), Innsbruck, Austria, February 1992, p. 248–250.
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Bulsari, A.B., Saxén, H. (1993). A Neural Network Based Control of a Simulated Biochemical Process. In: Albrecht, R.F., Reeves, C.R., Steele, N.C. (eds) Artificial Neural Nets and Genetic Algorithms. Springer, Vienna. https://doi.org/10.1007/978-3-7091-7533-0_41
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DOI: https://doi.org/10.1007/978-3-7091-7533-0_41
Publisher Name: Springer, Vienna
Print ISBN: 978-3-211-82459-7
Online ISBN: 978-3-7091-7533-0
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