引用本文:赵琳琳,方一鸣,仲伟峰,范志远.冷带轧机厚控系统自适应鲁棒输出反馈动态控制器设计[J].控制理论与应用,2008,25(4):787~790.[点击复制]
ZHAO Lin-lin,FANG Yi-ming,ZHONG Wei-feng,FAN Zhi-yuan.Design of adaptive robust output feedback dynamic controller for thickness control in a cold strip rolling mill[J].Control Theory and Technology,2008,25(4):787~790.[点击复制]
冷带轧机厚控系统自适应鲁棒输出反馈动态控制器设计
Design of adaptive robust output feedback dynamic controller for thickness control in a cold strip rolling mill
摘要点击 1478  全文点击 1166  投稿时间:2007-06-19  修订日期:2007-09-26
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DOI编号  
  2008,25(4):787-790
中文关键词  冷带轧机  厚度控制系统  鲁棒输出反馈动态控制  自适应控制  不确定系统
英文关键词  cold strip rolling mill  thickness control system  robust output feedback dynamic control  adaptive control  uncertain system
基金项目  河北省自然科学基金资助项目(F2005000389).
作者单位E-mail
赵琳琳 燕山大学 电气工程学院, 河北 秦皇岛 066004 0416zhaolin@163.com 
方一鸣 燕山大学 电气工程学院, 河北 秦皇岛 066004 fyming@ysu.edu.cn 
仲伟峰 哈尔滨理工大学 自动化学院, 黑龙江 哈尔滨 150080 zwfhrb@sina.com 
范志远 燕山大学 电气工程学院, 河北 秦皇岛 066004 fzy8508593@yahoo.com.cn 
中文摘要
      冷带轧机厚控系统可被认为是一个受外界干扰的线性不确定时滞系统. 本文首先设计了标称系统下的鲁棒输出反馈动态控制器, 以改善闭环系统的动静态性能; 其次, 在系统不需要满足不确定性匹配条件的情况下, 将参数和外部扰动不确定性综合考虑, 应用Lyapunov稳定性理论设计了系统不确定性上界参数的自适应估计器和系统的自适应控制器, 保证了闭环系统的渐近稳定性, 减小了设计的保守性; 两者结合实现了板带出口厚度的有效控制.最后通过一个仿真实例说明本文所提出的自适应鲁棒控制器的有效性.
英文摘要
      The thickness control system of cold strip rolling mill can be considered a linear uncertainty time-delay system with external disturbance. Firstly, robust output feedback dynamic controller for nominal system is designed to improve the dynamic and static performance of closed-loop system. The uncertainty matching condition is not necessary, and the parameter adaptive estimator law for uncertainty upper bound and adaptive controller are then designed on the basis of Lyapunov stability theory by taking parameter and disturbance uncertainty into account together. So the asymptotic stability of closed-loop system is guaranteed, and design conservation is reduced. Effective thickness control is also fulfilled for the exit strip by the robust output feedback dynamic controller and the adaptive controller. Finally, a simulation example is given to illustrate the efficacy of the proposed adaptive robust controller.