Optimal N-Parametric Type Iterative Learning Control

被引：13
|
作者：
Madady, Ali [1 ]
Reza-Alikhani, Hamid-Reza [1 ]
Zamiri, Sara [2 ]
机构：
[1] Tafresh Univ, Dept Elect Engn, Tehran Ave, Tafresh, Iran
[2] Islamic Azad Univ, Dept Control Engn, Boroujerd Branch, Boroujerd, Iran
来源：
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS | 2018年 / 16卷 / 05期
关键词：
Iterative learning control; monotonic convergence; multi parametric controller; optimal design; DISCRETE-TIME-SYSTEMS; MULTIAGENT SYSTEMS; CONTROL FRAMEWORK; CONTROL DESIGN; OPTIMIZATION; TRACKING; SEEKING; ROBOTS;
D O I：
10.1007/s12555-017-0259-z
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
One of the most important problems in the field of the iterative learning control (ILC) is to design algorithms, in order to achieve a desired convergence rate. In this paper a new type of the ILC algorithm is introduced, which is called N-parametric type ILC with optimal gains. The convergence of the proposed algorithm is analyzed and an optimal design method is presented to determine its gains. The effect of the number of the parameters on the convergence rate of the presented ILC is investigated. It is shown that N parametric type of this ILC has a better performance than the N-1 one. Illustrative simulation examples are given to verify the theoretical analysis.
引用
收藏
页码：2187 / 2202
页数：16
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