Explicit Model Predictive Controller Design for Thickness and Tension Control in a Cold Rolling Mill

作     者：Ogasahara, Tomoyoshi Hovd, Morten Asano, Kazuya 

作者机构：Instrument and Control Engineering Research Dept. Steel Research Lab. JFE Steel Corp. FukuyamaHiroshima721-8510 Japan Department of Engineering Cybernetics Norwegian University of Science and Technology TrondheimN-7491 Norway Steel Research Lab. JFE Steel Corp. KawasakiKanagawa210-0855 Japan 

出 版 物：《IFAC-PapersOnLine》 

年 卷 期：2016年第49卷第20期

页      面：126-131页

核心收录：

主　　题：Controllers Cold rolling Cold rolling mills Iron and steel industry MIMO systems Model predictive control Predictive control systems Process control Steelmaking Approximation errors Control objectives Controller designs Explicit model predictive control Multi input/multi output systems Optimal controls Predictive control Process model 

摘      要：This paper addresses modeling of a cold rolling mill and controller design based on explicit model predictive control(explicit MPC). The control objectives are to track the exit thickness to the reference with high accuracy with minimized strip tension deviation. In the simulation, good control is obtained when the disturbance entering the system is small enough. However, the thickness shows the offset from the reference in case of acceleration, because the approximation error of the linearized model increases and it is different from the model in the design of the controller. In order to compensate for the control offset, an additional integral logic using the estimation error of exit thickness is proposed. The validity of this approach was verified by simulation and offset free control was achieved. © 2016