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

页码：999 / 1007

页数：9