Linear multivariable dynamic model of a hot strip finishing mill

Abstract

A steel hot strip finishing mill presents significant interactions between variables that considerably reduce performance. Traditionally, the control techniques implemented are based on classical approaches assuming an ideal model. Modelling interactions would allow the opportunity to suppress them by the application of modern multivariable control techniques. In this paper the derivation of a linearized multivariable model of a real-life hot strip mill based on previous schemes is presented as a case study. Linearization of the nonlinear static relations around an operating point is performed. The operating conditions are the mill set-up calculations obtained from rolling schedules and non-linear relations used in the plant. Some useful details for practitioners are given. Simulations and experimental model validation are also presented. Since the mill in the real hot rolling line is in closed loop, it is not possible to carry out an experimental validation of the plant itself (i.e. in open loop); therefore, the model was experimentally validated in closed loop. As an example of the use of the multivariable model an H ' multivariable optimal controller to attain nominal performance is designed for the looper system and results are presented.

Parametric Robust Control of the Multivariable 2 × 2 Looper System in Steel Hot Rolling: A Comparison between Multivariable QFT and H∞

“…Two FM contiguous stands, i and i + 1, and the lopper i between them were represented by a linear 4 × 4 multivariable model [2]. The assumption of a linear behavior is realistic, since the mill operates under small signal regime once the steel bar has been threaded.…”

“…A hot strip mill (HSM) is a process that rolls steel slabs into coiled strips. The finishing mill (FM), where the strip takes the final thickness, is the most critical process in an HSM because of the great number of variables involved, interactions between them, and hence its modeling complexity and uncertainty [1,2]. On the other hand, as with many other industrial processes, the environment is highly noisy.…”

“…During the past two decades, control of relevant aspects related to thickness has been an active research topic in the literature [3][4][5][6][7][8]. Special attention has been paid to the looper system variables, tension and looper angular position, owing mainly to their great influence on strip thickness and finishing temperature [2]. Several control approaches for these variables with the aim of achieving stability and performance in the presence of uncertainties and interactions have been proposed.…”

“…The controllers are also compared with PI controllers, which are the current controllers in most HSMs worldwide, and the two SISO QFT controllers presented in [18], when applicable; evaluating in this way, the potential benefits of compensating for interactions and parameter uncertainty. The multivariable linearized HSM model presented and experimentally validated in Obregon et al [2] has been built in Simulink to perform time domain tests.…”

Control of Strip Tension in a Rolling Mill Based on Loopers and Impedance Control

“…In more advanced multivariable control systems, the interaction between strip thickness, roll speed, roll gap dimensions, strip tension, and looper angle is systematically taken into account. Mathematical models that describe these interactions are typically derived by linearization at the respective operating point (Hearns et al, 2009;Obregón et al, 2010) or along an operating trajectory (Pittner and Simaan, 2010). Based on such models, the design of H ∞ -controllers (Imanari et al, 1997) or linearquadratic-regulator-type (LQR) controllers (Miura et al, 1993;Okada et al, 1998;Pittner and Simaan, 2010) for strip thickness, strip tension, and looper angle is common practice.…”