Direct Width Control Systems Based on Width Prediction Models in Hot Strip Mill

In this paper, a width control system is proposed to obtain the desirable width margin of a strip in the rolling process of the hot strip mill. A simplified FEM (Finite Element Method) based width prediction model (WPM) is developed to compute the width spread at each stand. A neural network based error correction model (ECM) is also introduced to compensate for modelling errors from the simplified FEM based WPM. Input variables for the neural network model are chosen by using the hypothesis testing. In addition, the width control scheme using the simplified FEM based WPM and the neural network based ECM is proposed to achieve the desired width margin in the finishing mill. It is shown through the field test of the Pohang no. 1 hot strip mill of POSCO that the performance with respect to the width margin is greatly improved by the proposed width control scheme based on two models.