The analysis of convergence speed for a higher order iterative learning control algorithm

被引：0
|
作者：
Wang, Dong [1 ]
Xu, Jinxue
Li, Shujiang
机构：
[1] Shenyang Univ Technol, Sch Informat Sci & Engn, Shenyang 110023, Peoples R China
[2] Sanyo Elect Co Ltd, Dalian 116600, Peoples R China
来源：
DYNAMICS OF CONTINUOUS DISCRETE AND IMPULSIVE SYSTEMS-SERIES B-APPLICATIONS & ALGORITHMS | 2006年 / 13E卷
关键词：
D O I：
暂无
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
A higher order open-closed-loop iterative learning control law is proposed in the presence of the system uncertainties. By means of contraction mapping principle and robust optimal design method, it is proven that the proposed algorithm is convergent, that the algorithm can speed up the convergence rate of iterative learning control in the iteration domain and converges faster than an open-loop iterative learning control algorithm, and that the lower the order of the algorithm is, the faster its convergent rate is. It is very first order algorithm that is the fastest. The simulation results show the effectiveness of the algorithm.
引用
收藏
页码：2732 / 2736
页数：5
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