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A neural network model based predictive control approach: application to a semi-batch reactor.
- Source :
- International Journal of Advanced Manufacturing Technology; Jul2005, Vol. 26 Issue 1/2, p161-168, 8p
- Publication Year :
- 2005
-
Abstract
- Neural networks can be considered to be new modelling tools in process control and especially in non-linear dynamical systems cases. Their ability to approximate non-linear functions has been very often demonstrated and tested by simulation and experimental studies. In this paper, a predictive control strategy of a semi-batch reactor based on neural network models is proposed. Results of a non-linear control of the reactant temperature of a semi-batch reactor are presented. The process identification is composed of an off-line phase that consists in training the network, and of an on-line phase that corresponds to the neural model adaptation so that it fits any modification of the process dynamics. Experimental results when using this method to control a semi-batch reactor are reported and show the great potential of this strategy in controlling non-linear processes. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 02683768
- Volume :
- 26
- Issue :
- 1/2
- Database :
- Complementary Index
- Journal :
- International Journal of Advanced Manufacturing Technology
- Publication Type :
- Academic Journal
- Accession number :
- 17551416
- Full Text :
- https://doi.org/10.1007/s00170-003-1972-8