Improvement of a Mathematical Model and Model Predictive Control for Strip Steering Control in Hot Strip Finishing Mill

Abstract

Strip walking is an unstable lateral movement in a hot strip finishing mill that causes the strip to crash into the side guides, resulting in a tail pinch where the strip is rolled in a folded state. Strip walking should be appropriately controlled to prevent tail pinches, and an adequate mathematical model is essential to design the strip steering control. In this paper, the traditional model and a recently proposed model representing strip walking are numerically compared, and the latter is shown to characterize the details of the actual phenomenon. Such a mathematical model derivation makes it possible to use model predictive control to optimally control the strip walking, considering the rate limit constraint of the actuator. However, model predictive control requires time-consuming optimization computation. Thus, control performance deteriorates with longer control periods. In this paper, we propose a new model prediction control method to reduce optimization computation time with discretized control input that enables fast discrete optimization instead of slow continuous optimization. It is also shown that fixing the misalignment between the roll and steel strip centers is insufficient to prevent the tail pinch. Moreover, it is vital to suppress the rotational motion of the steel strip by using numerical simulations.