Kazuyoshi Kimura

Shrinkage Prediction of a Steel Production via Model-On-Demand

Abstract In this paper, a prediction method for shrinkage of steel production via the so-called Model-on-Demand is proposed. The basic idea of the proposed method is to build a local weighted model from all observed data stored in a database when a prediction of shrinkage is needed. The usefulness of the proposed method is illustrated by a simulation study with the observed data sets which were measured in the actual steel works.

Identification Technology of Frequency Response of Plant in Steel Rolling Process

Abstract An identification method of the frequency responses of actual plant was investigated for steel rolling control system. It is important for achieving the highest control accuracy to identify the frequency responses of actual plant and to design and to tune the controller of the system properly. Therefore, according to various rolling data measured during really operating, identification method based on extended least-squares method which estimates the parameters of ARMAX model under condition of the specified steady state gain constraint of the controlled system was tried. And the effectiveness of this method for the feed-forward gage control system of the reversing cold mill was certified.