Norm-Optimal Iterative Learning Control With Intermediate Point Weighting: Theory, Algorithms, and Experimental Evaluation

被引：67
|
作者：
Owens, David H. [1 ,2 ]
Freeman, Christopher T. [2 ]
Thanh Van Dinh [2 ]
机构：
[1] Univ Sheffield, Dept Automat Control & Syst Engn, Sheffield S1 3JD, S Yorkshire, England
[2] Univ Southampton, Sch Elect & Comp Sci, Southampton SO17 1BJ, Hants, England
来源：
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY | 2013年 / 21卷 / 03期
关键词：
Iterative learning control (ILC); iterative methods; learning control systems; linear systems; motion control; non-minimum phase systems; optimization methods; test facilities; ILC; DESIGN;
D O I：
10.1109/TCST.2012.2196281
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This brief considers the iterative learning control (ILC) problem when tracking is only required at a subset of isolated time points along the trial duration. It presents a norm-optimal ILC solution to the problem with well-defined convergence properties, design guidelines, and supporting experimental results using an electromechanical test facility.
引用
收藏
页码：999 / 1007
页数：9
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