An indirect iterative learning controller for nonlinear systems with mismatched uncertainties and matched disturbances

被引：3

作者：

Trung Thanh Cao ^{[1
]}

Phuoc Doan Nguyen ^{[1
]}

Nam Hoai Nguyen ^{[1
]}

Ha Thu Nguyen ^{[1
]}

机构：

[1] Hanoi Univ Sci & Technol, Sch Elect & Elect Engn, Dept Automat Engn, Hanoi 11615, Vietnam

来源：

INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE | 2022年 / 53卷 / 16期

关键词：

Disturbance compensation; indirect ILC; sampled data system; TRAJECTORY TRACKING; STATE STABILITY; DESIGN; INPUT;

D O I：

10.1080/00207721.2022.2083259

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The article proposes an intelligent controller for output regulation of nonlinear non-autonomous continuous-time systems with mismatched uncertainties and matched disturbances. This controller is established by firstly converting the original system into an input-to-state stable one via learning-based compensation of lumped system disturbances and then applying the standard P-type iterative learning control. The learning-based disturbance compensator is basically created with the numerical backward differentiation in iterative mode. The control performance of the obtained sampled data system using the proposed controller has been verified throughout both in theory and comparison with the existing method via numerical simulations.

引用

页码：3375 / 3389

页数：15

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