Sampled-data iterative learning control for nonlinear systems with arbitrary relative degree

被引：85

作者：

Sun, MX ^{[1
]}

Wang, DW ^{[1
]}

机构：

[1] Nanyang Technol Univ, Sch Elect & Elect Engn, Singapore 639798, Singapore

来源：

AUTOMATICA | 2001年 / 37卷 / 02期

关键词：

learning control; convergence; relative degree; sampled-data; nonlinear systems;

D O I：

10.1016/S0005-1098(00)00141-2

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, a sampled-data iterative learning control method is proposed for nonlinear systems without restriction on system relative degree. The learning algorithm does not require numerical differentiations of any order from the tracking error. A sufficient condition is derived to guarantee the convergence of the system output at each sampling instant to the desired trajectory. Numerical simulation is conducted to demonstrate the theoretical result. (C) 2000 Elsevier Science Ltd. All rights reserved.

引用

页码：283 / 289

页数：7

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