Identification and optimization for hydraulic roll gap control in strip rolling mill
来源期刊：中南大学学报(英文版)2015年第6期
论文作者：SUN Jie CHEN Shu-zong HAN Huan-huan CHEN Xing-hua CHEN Qiu-jie ZHANG Dian-hua
文章页码：2183 - 2191
Key words：hydraulic roll gap control; modeling; system identification; generalized predictive control
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.
SUN Jie(孙杰), CHEN Shu-zong(陈树宗), HAN Huan-huan(韩欢欢), CHEN Xing-hua(陈兴华), CHEN Qiu-jie(陈秋捷), ZHANG Dian-hua(张殿华)
(State Key Laboratory of Rolling and Automation (Northeastern University), Shenyang 110819, China)
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.
Key words:hydraulic roll gap control; modeling; system identification; generalized predictive control
