Enhancing trajectory tracking for a class of process control problems using iterative learning

被引：18

作者：

Xu, JX ^{[1
]}

Lee, TH ^{[1
]}

Tan, Y ^{[1
]}

机构：

[1] Natl Univ Singapore, Dept Elect Engn, Singapore 119260, Singapore

来源：

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE | 2002年 / 15卷 / 01期

关键词：

enhance tracking; filter-based iterative learning control; frequency convergence analysis;

D O I：

10.1016/S0952-1976(02)00008-8

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A method of enhancing tracking in repetitive processes, which can be approximated by a first-order plus dead-titne model is presented. Enhancement is achieved through filter-based iterative learning control (ILC). The design of the ILC parameters is conducted in frequency domain, which guarantees the convergence property in iteration domain. The filter-based ILC can be easily added to existing control systems. To clearly demonstrate the features of the proposed ILC, a water heating process under a PI controller is used as a testbed. The empirical results show improved tracking performance with iterative learning. (C) 2002 Elsevier Science Ltd. All rights reserved.

引用

页码：53 / 64

页数：12

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