Iterative Learning Control for Distributed Parameter Systems Based on Non-Collocated Sensors and Actuators

被引：0

作者：

Jianxiang Zhang ^{[1
]}

Baotong Cui ^{[1
]}

Xisheng Dai ^{[2
]}

Zhengxian Jiang ^{[3
]}

机构：

[1] the Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), School of Internet of Things Engineering, Jiangnan University

[2] the School of Electrical and Information Engineering, Guangxi University of Science and Technology

[3] the School of Science, Jiangnan University

来源：

IEEE/CAA Journal of Automatica Sinica | 2020年 / 7卷 / 03期

基金：

中国国家自然科学基金;

关键词：

Actuators; distributed parameter system; iterative learning control; PD-type ILC scheme; sensors;

D O I：

暂无

中图分类号：

TP13 [自动控制理论]; TP212 [发送器（变换器）、传感器];

学科分类号：

0711 ; 071102 ; 080202 ; 0811 ; 081101 ; 081103 ;

摘要：

In this paper, an open-loop PD-type iterative learning control(ILC) scheme is first proposed for two kinds of distributed parameter systems(DPSs) which are described by parabolic partial differential equations using non-collocated sensors and actuators. Then, a closed-loop PD-type ILC algorithm is extended to a class of distributed parameter systems with a non-collocated single sensor and m actuators when the initial states of the system exist some errors. Under some given assumptions, the convergence conditions of output errors for the systems can be obtained. Finally, one numerical example for a distributed parameter system with a single sensor and two actuators is presented to illustrate the effectiveness of the proposed ILC schemes.

引用

页码：865 / 871

页数：7

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