Mold Level Control in Continuous Caster by Neural Network Model

Abstract

In continuous billet casting, keeping the mold level steady is one of the most important technologies for maintaining steel quality. Using conventional methods, it is difficult to attain precise control of the mold level because of the nonlinear characteristics of the process. We have developed a control system using a neural network model to overcome this problem. In this paper, control problems of a continuous caster are introduced first. Next, the structure of the control system is proposed. In our proposed system, the neural network model recognizes the temporal patterns of inlet flow and controls the stopper stroke for a main control loop with a PI controller. The problems involved in construction of a valid neural network model that has good generalization and robust properties, are discussed from the viewpoint of optimizing the number of hidden layer units by the information criterion. Finally some results of its application are described.