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
收藏
页码：53 / 64
页数：12
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