Title :
Proportional correction rule for the control design of manufacturing systems using neural networks
Author :
Haouani, M. ; Lefebvre, D. ; Zerhouni, N. ; El Moudni, A.
Author_Institution :
Belfort Technopole, L.M.P-EniBelfort, France
Abstract :
Presents a control design for a particular class of manufacturing systems modeled by artificial neural networks. A dynamic implementation of manufacturing systems deduced from a modular approach of modeling using neural networks is described. An adaptive control is applied on the network model of the system. The proposed control is inspired from the learning property of neural networks. The obtained results are illustrated on an industrial manufacturing system
Keywords :
adaptive control; neurocontrollers; process control; production control; proportional control; adaptive control; control design; learning property; manufacturing systems; modular approach; proportional correction rule; Adaptive control; Artificial neural networks; Control design; Control systems; Electrical equipment industry; Electronic mail; Machinery production industries; Manufacturing systems; Neural networks; Open loop systems;
Conference_Titel :
Neural Networks Proceedings, 1998. IEEE World Congress on Computational Intelligence. The 1998 IEEE International Joint Conference on
Conference_Location :
Anchorage, AK
Print_ISBN :
0-7803-4859-1
DOI :
10.1109/IJCNN.1998.682236
