Title :
Neuro-fuzzy tension controller for tandem rolling
Author :
Janabi-Sharifi, F. ; Liu, J.
Author_Institution :
Dept. of Mech. Aerosp. & Ind. Eng., Ryerson Univ., Toronto, Ont., Canada
Abstract :
A fuzzy logic controller (FLC) is designed to maintain constant tension for tandem rolling mills. By envisioning the fuzzy inference system as a neural network and introducing a tutor, a backward propagation algorithm is used as a self-organization technique for the FLC to approach the best parameters under supervision. Simulation results exhibit the generalization and adaptivity of the neuro-fuzzy controller in offline tuning.
Keywords :
backpropagation; fuzzy control; fuzzy neural nets; generalisation (artificial intelligence); neurocontrollers; nonlinear control systems; rolling mills; strain control; adaptivity; backward propagation algorithm; complex nonlinear rolling process; constant tension; fuzzy inference system; fuzzy logic controller; generalization; neural network; neuro-fuzzy tension controller; offline tuning; self-organization technique; simulation results; tandem rolling mills; Artificial neural networks; Automatic speech recognition; Control systems; Fuzzy control; Fuzzy logic; Fuzzy neural networks; Humans; Milling machines; Resonance; Working environment noise;
Conference_Titel :
Intelligent Control, 2002. Proceedings of the 2002 IEEE International Symposium on
Print_ISBN :
0-7803-7620-X
DOI :
10.1109/ISIC.2002.1157781
