Iterative learning control for linear discrete-time systems with high relative degree under initial state vibration

被引：28

作者：

Wei, Yun-Shan ^{[1
]}

Li, Xiao-Dong ^{[1
]}

机构：

[1] Sun Yat Sen Univ, Sch Data & Comp Sci, Guangzhou 510006, Guangdong, Peoples R China

来源：

IET CONTROL THEORY AND APPLICATIONS | 2016年 / 10卷 / 10期

基金：

中国国家自然科学基金;

关键词：

linear systems; MIMO systems; iterative learning control; discrete time systems; linear discrete-time systems; high relative degree under initial state vibration; linear discrete-time multiple-input-multiple-output; average operator-based iterative learning control algorithms; ILC tracking error; ILC laws; initial rectifying action; reference trajectory tracking; linear discrete-time MIMO systems; NONLINEAR-SYSTEMS; CONVERGENCE;

D O I：

10.1049/iet-cta.2015.0826

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

For linear discrete-time multiple-input-multiple-output (MIMO) systems with high relative degree, this study presents three average operator-based iterative learning control (ILC) algorithms to investigate the effect of initial state vibration on ILC tracking error. The proposed ILC laws include an initial rectifying action against initial state vibration at certain time points, and pursue the reference trajectory tracking beyond the initial time points. It is proved that, when the proposed ILC laws are applied to linear discrete-time MIMO systems with high relative degree, the effect of the initial state vibration on ILC tracking error beyond the initial time points can be exactly decided. Moreover, the ILC tracking error beyond the initial time points can be driven to zero against a progressive fixed initial state error. Numerical examples are used to illustrate the effectiveness of the proposed ILC laws.

引用

页码：1115 / 1126

页数：12

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