Analysis of Grey Prediction Based Iterative Learning Control

摘要：

This paper presents a novel iterative learning control method based on the research of grey theory.The grey predictor is applied to extract key information and reduce the randomness of the measured non-stationary time series signals from sensors,and send the prediction information to the iterative learning controller.This design can not only reduce the trajectory tracking error of reference input but also improve the learning rate.The complete mathematical model is derived and the sufficient condition for convergence is given.At last, experimental results obtained from two plants show that the tracking accuracy is much improved when the proposed new method is applied.

关键词： Iterative learning control grey prediction accumulated generation operation convergence rate

作者: Lisheng Wei Minrui Fei Wanqing Zhao

作者单位: Shanghai Key Laboratory of Power Station Automation Technology School of Mechatronics and Automation,Shanghai University Shanghai 200072,P.R.China

会议类型: 国际会议

会议名称: 2008 IEEE International Conference on Onformation and Automation(IEEE 信息与自动化国际会议)

会议地点: 张家界

会议语种:英文

页码: 1096-1100

在线出版日期: 2008-06-20（万方平台首次上网日期，不代表论文的发表时间）