Title :
Shape control of rolling mills by a neural and fuzzy hybrid architecture
Author_Institution :
Res. Lab., Hitachi Ltd., Ibaraki, Japan
Abstract :
Hitachi Ltd has developed pattern recognition and control techniques which combine neural network and fuzzy logic. Conventionally, skilled operators recognize and manually control waveform patterns based on their sense and experience. The new system recognizes and controls waveform patterns by means of neural networks and fuzzy logics to realize fully automatic shape control of rolling mills. The neural network recognizes spatially distributed waveform patterns from sensor signals, and the fuzzy logics operate multiple final control elements for automatic pattern control. The developed control technique has been applied to automatic shape control system for a Sendzimir Rolling Mill. Shape control for this type of rolling mill is difficult with conventional automatic control systems because of complicated rolling phenomena and the difficulty of creating a control models. Tests with an actual rolling system proved that the new technique achieves more accurate control than the conventional manual operation by skilled operators. The system has been applied at a few plants and is operating favorably
Keywords :
fuzzy control; fuzzy logic; neurocontrollers; pattern recognition; rolling mills; steel industry; waveform analysis; Sendzimir Rolling Mill; automatic pattern control; automatic shape control system; complicated rolling phenomena; fully automatic shape control; fuzzy hybrid architecture; fuzzy logic; multiple final control elements; neural network; pattern recognition; rolling mills; sensor signals; spatially distributed waveform pattern recognition; Automatic control; Control systems; Fuzzy control; Fuzzy logic; Manuals; Milling machines; Neural networks; Pattern recognition; Shape control; System testing;
Conference_Titel :
Fuzzy Systems, 1995. International Joint Conference of the Fourth IEEE International Conference on Fuzzy Systems and The Second International Fuzzy Engineering Symposium., Proceedings of 1995 IEEE Int
Conference_Location :
Yokohama
Print_ISBN :
0-7803-2461-7
DOI :
10.1109/FUZZY.1995.410036