Identification and optimization for hydraulic roll gap control in strip rolling mill

Abstract

In order to improve the control performance of strip rolling mill, theoretical model of the hydraulic gap control (HGC) system was established. HGC system offline identification scheme was designed for a tandem cold strip mill, the system model parameters were identified by ARX model, and the identified model was verified. Taking the offline identified parameters as the initial values, online identification using recursive least square was carried out with model parameters changing. For the purpose of improving system robustness and decreasing the sensitivity due to model errors, the HGC system based on generalized predictive control (GPC) was designed, and simulation experiments for traditional controller and GPC controller were conducted. The results show that both controllers acquire good control effect with model matching. When the model mismatches, for the traditional controller, the overshot will increase to 76.7% and the rising time will increase to 165.7 ms, which cannot be accepted by HGC system; for the GPC controller, the overshot is less than 8.5%, and the rising time is less than 26 ms in any case.

Keywords

hydraulic roll gap control / modeling / system identification / generalized predictive control

References

[1] HAMIDR K, FARIDS, SAEEDH. Unified gauge-tension control in cold rolling mills: A robust regulation technique [J]. International Journal of Precision Engineering and Manufacturing, 2011, 12(3): 393-403

[2] JOHNP, MARWANA S. Control of a continuous tandem cold metal rolling process [J]. Control Engineering Practice, 2008, 2: 1379-1390

[3] JOHNP, NICHOLASS S, MarwanA S. A new strategy for optimal control of continuous tandem cold metal rolling [J]. IEEE Transactions on Industry Application, 2010, 46(2): 703-711

[4] KIMY D, KIMC W, LEES J, PARKH C. Dynamic modeling and numerical analysis of a cold rolling mill [J]. International Journal of Precision Engineering and Manufacturing, 2013, 14(3): 407-413

[5] HOSHINOI, MEAKAWAY, FUJIMOTOT. Observer based multivariable control of the aluminum cold tandem mill [J]. Automatica, 1997, 24(6): 741-754

[6] LEEW H, LEES R. Computer simulation of dynamic characteristics of tandem cold rolling process [J]. KSME International Journal, 1999, 13(8): 616-624

[7] ZHOUM-l, TIANY-t, GAOW, YANGZ-gang. High precise control method for a new type of piezoelectric electro-hydraulic servo valve [J]. Journal of Central South University of Technology, 2007, 14(6): 832-837

[8] LIUG-m, DIH-s, ZHOUC-l, LIH-c, LIUJiang. Tension and thickness control strategy analysis of two stands reversible cold rolling mill [J]. Journal of Iron and Steel Research, 2012, 19(10): 20-25

[9] SUNJ, ZHANGD-h, LIX, ZHANGJ, DUD-shun. Smith prediction monitor AGC system based on fuzzy self-tuning PID control [J]. Journal of Iron and Steel Research International, 2010, 17(2): 22-26

[10] SUNJ-l, PENGY, LIUH-min. Dynamic characteristics of cold rolling mill and strip based on flatness and thickness control in rolling process [J]. Journal of Central South University, 2014, 21(2): 567-576

[11] RENY, RUANJ, JIAW-ang. Output waveform analysis of an electro-hydraulic vibrator controlled by the multiple valves [J]. Chinese Journal of Mechanical Engineering, 2014, 27(1): 186-197

[12] LIM-w, LIUH-f, WANGX-l, YINF-f, BIANX-x, ZHANGL, TONGC-nan. Key techniques of automatic gauge control and profile control for aluminium strip and foil [J]. Transactions of Nonferrous Metals Society of China, 2006, 16(3): 1595-1599

[13] DYJAH, MARKOWSKIJ, STOINSKID. Asymmetry of the roll gap as a factor improving work of the hydraulic gauge control in the plate rolling mill [J]. Journal of Materials Processing Technology, 1996, 60(3): 73-80

[14] ZHANGW, WANGY-q, SUNM-hui. Modeling and simulation of electric hydraulic servo valve control system for hydraulic bending roll system [J]. China Mechanical Engineering, 2009, 20(3): 345-348

[15] WANGC-hang. Hydraulic control system [M]. Beijing: China Machine Press, 2011

[16] LVY-song. Modeling in frequency domain for valve controlled asymmetric hydraulic cylinders [J]. Chinese Journal of Mechanical Engineering, 2007, 43(9): 122-126

[17] ANDREWA, RUIL. Amplified approach to force control for electro-hydraulic systems [J]. Control Engineering Practice, 2000, 8: 1347-1356

[18] HEX-y, HEQ-h, ZOUX-f, XIEX-h, HUANGZ-xiong. Fault diagnosis approach of hydraulic system using RBF network and ARX model [J]. Journal of System Simulation, 2009, 21(1): 282-285

[19] GUNTERW R, HEINRICHR A, WOLFGANGS, KARLA, KARLH W. Improved rolling mill automation by means of advanced control techniques and dynamic simulation [J]. IEEE Transaction of Industry Application, 1996, 32(3): 599-607

[20] GUIW-h, SONGH-y, YANGC-hua. Identification algorithm of Hammerstein-Wiener model with process noise and its convergence analysis [J]. Control Theory and Applications, 2008, 25(3): 393-397

[21] YOUNESM A, SHAHTOUTM, DAMIRM N. A parameters design approach to improve product quality and equipment performance in hot rolling [J]. Journal of Materials Processing Technology, 2006, 171(1): 83-92

[22] CAMACHOE F, RAMIREZD R, LIMOND, MUNOZP, ALAMOT. Model predictive control techniques for hybrid systems [J]. Annual Reviews in Control, 2010, 34(2): 21-31