DocumentCode
376234
Title
A neural-net based self-tuning fuzzy looper control for rolling mills
Author
Janabi-Sharifi, E.
Author_Institution
Dept. of Mech. Aerosp. & Ind. Eng., Ryerson Univ., Toronto, Ont., Canada
Volume
1
fYear
2001
fDate
2001
Firstpage
87
Abstract
Looper control is one of the challenging problems in rolling mills. The purpose of the paper is to propose an intelligent control method using fuzzy logic and neural networks for improved the performance of looper control over conventional loop control methods. The focus of the paper is on the rule-tuning aspect of the proposed fuzzy looper control. Simulation results are presented to verify the performance of the control system
Keywords
fuzzy control; neurocontrollers; process control; rolling mills; self-adjusting systems; tuning; fuzzy control; intelligent control; loop control; neural network; neurocontrol; process control; rolling mills; Automatic control; Control system synthesis; Control systems; Fuzzy control; Milling machines; Robotics and automation; Service robots; Steel; Strips; Tuning;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems, Man, and Cybernetics, 2001 IEEE International Conference on
Conference_Location
Tucson, AZ
ISSN
1062-922X
Print_ISBN
0-7803-7087-2
Type
conf
DOI
10.1109/ICSMC.2001.969793
Filename
969793
Link To Document