DocumentCode
2222003
Title
Optimisation of a polymer plant by an embedded hybrid architecture
Author
Meert, Kurt ; Van Bael, Patrick ; Rijckaert, Marcel
Author_Institution
Expert Syst. Appl. Dev. Group, Katholieke Univ., Leuven, Heverlee, Belgium
Volume
1
fYear
1998
fDate
4-8 May 1998
Firstpage
719
Abstract
In this paper a hybrid architecture is developed to optimise set-point changes between different polyethylene brands. This architecture combines two different AI-techniques: a recurrent neural network, which is used to model the polyethylene plant; and a simulated annealing-based optimisation algorithm. Several experiments were performed to demonstrate the capabilities of this hybrid optimisation architecture
Keywords
chemical variables control; neurocontrollers; plastics industry; process control; real-time systems; recurrent neural nets; simulated annealing; embedded hybrid architecture; optimisation; plastics industry; polyethylene plant; polymer; process control; recurrent neural network; set-point control; simulated annealing; Expert systems; Inductors; Neural networks; Optimal control; Polyethylene; Polymers; Predictive models; Production; Recurrent neural networks; Simulated annealing;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks Proceedings, 1998. IEEE World Congress on Computational Intelligence. The 1998 IEEE International Joint Conference on
Conference_Location
Anchorage, AK
ISSN
1098-7576
Print_ISBN
0-7803-4859-1
Type
conf
DOI
10.1109/IJCNN.1998.682369
Filename
682369
Link To Document