A neural network model based predictive control approach: application to a semi-batch reactor

被引:7
作者
M'Sahli, F [1 ]
Matlaya, R
机构
[1] High Inst Technol Studies Ksar Hellal, Ksar Hellal 5070, Monastir, Tunisia
[2] Univ Sfax, Natl Sch Engn Gabes, Gabes 6029, Tunisia
关键词
neural networks; non-linear control; predictive control; reactor;
D O I
10.1007/s00170-003-1972-8
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:161 / 168
页数:8
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