Neural networks for process control of flat film extrusion systems

被引:0
作者
Baginski, SM
Kochs, HD
机构
来源
FIRST INTERNATIONAL CONFERENCE ON KNOWLEDGE-BASED INTELLIGENT ELECTRONIC SYSTEMS, PROCEEDINGS 1997 - KES '97, VOLS 1 AND 2 | 1997年
关键词
neural networks; flat film extrusion systems; adaptive process control; nonlinear system modelling;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper focuses on the improvement of an existing nonlinear control system with neural nets. Crucial for the successfull exploitation of the improvement potential is the Neural Networks outstanding capability for on-line adaption and the possibility to combine Neural Networks with existing physical or mathematical models. The primarily result is an improved process modelling which allows process model adaption, Using the described capabilities a predictive feedforward control/feedbackward control(FFC/FFB) has been developed to overcome the greatest problems in processes with long delay times. The corresponding installation is a flat film extrusion system to produce polymer sheets, Simulation results point out that optimized process control in flat film production can lead to significant material savings as well as significant improvements in product quality.
引用
收藏
页码:581 / 587
页数:7
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