Iterative learning control in optimal tracking problems with specified data points

被引：84

作者：

Son, Tong Duy ^{[1
]}

Ahn, Hyo-Sung ^{[1
]}

Moore, Kevin L. ^{[2
]}

机构：

[1] GIST, Sch Mechatron, Kwangju 500712, South Korea

[2] Colorado Sch Mines, Coll Engn & Computat Sci, Golden, CO USA

来源：

AUTOMATICA | 2013年 / 49卷 / 05期

基金：

新加坡国家研究基金会;

关键词：

Iterative learning control; Specified data points; Optimal tracking;

D O I：

10.1016/j.automatica.2013.02.008

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, we present two iterative learning control (ILC) frameworks for tracking problems with specified data points that are desired points at certain time instants. To design ILC systems for such problems, unlike traditional ILC approaches, we first develop an algorithm in which not only the control signal but also the reference trajectory is updated at each trial. We investigate the relationship between the reference trajectory and ILC tracking control as it relates to the rate of convergence. Second, a new ILC scheme is proposed to produce output curves that pass close to the desired points. Here, the control signals are generated by solving an optimal ILC problem with respect to the desired sampling points. One of the key advantages of the proposed approaches is a significant reduction of the computational cost. (c) 2013 Elsevier Ltd. All rights reserved.

引用

页码：1465 / 1472

页数：8

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