Shape control of rolling mills by a neural and fuzzy hybrid architecture

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. >