Title: Dynamic model building of thickness control system for four-high rolling mill and HCO_∞ robust controller design

Authors: Jianliang Sun, Yan Peng, Hongmin Liu

Addresses: State Key Laboratory of Metastable Materials Science and Technology, Engineering Research Center of Rolling Equipment and Complete Technology of Ministry of Education, Yanshan University, Qinhuangdao 066004, PR China. ' State Key Laboratory of Metastable Materials Science and Technology, Engineering Research Center of Rolling Equipment and Complete Technology of Ministry of Education, Yanshan University, Qinhuangdao 066004, PR China. ' State Key Laboratory of Metastable Materials Science and Technology, Engineering Research Center of Rolling Equipment and Complete Technology of Ministry of Education, Yanshan University, Qinhuangdao 066004, PR China

Abstract: In this paper, the integral dynamic model of four-high mill is built which includes the rolling process model, the dynamic model of mill stand-rolls and the dynamic model of hydraulic servo system. The three models are coupled and linearised, the MIMO transfer function of four-high mill system is obtained. Considering the quality of the product, the MIMO model is simplified and the thickness control system based on thickness gauge is derived. The H_∞ robust controller is designed for the thickness control system based on the mixed sensitivity robust control theory. The weighting functions are selected based on genetic algorithm. Simulation results and comparison with the effect of PI controller show that the robust controller designed has better disturbance attenuation performance for parameter uncertainty and external disturbance. The dynamics performances and stability of the thickness control system based on thickness gauge are improved significantly.

Keywords: dynamic modelling; genetic algorithms; GAs; H-infinity robust control; mixed sensitivity; mill stand-rolls; hydraulic servo systems; thickness control; simulation; rolling mills.

DOI: 10.1504/IJMIC.2009.027031

International Journal of Modelling, Identification and Control, 2009 Vol.7 No.1, pp.103 - 112

Published online: 13 Jul 2009 *

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