Adaptive tracking and recursive identification for Hammerstein systems

被引：45

作者：

Zhao, Wen-Xiao ^{[2
]}

Chen, Han-Fu ^{[1
]}

机构：

[1] Chinese Acad Sci, Key Lab Syst & Control, Inst Syst Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China

[2] Tsinghua Univ, Dept Automat, Beijing 100084, Peoples R China

来源：

AUTOMATICA | 2009年 / 45卷 / 12期

基金：

中国国家自然科学基金; 中国博士后科学基金;

关键词：

Hammerstein system; Weighted least squares; Adaptive tracking; Recursive identification; Optimality; Strong consistency; NONLINEAR-SYSTEMS; MODEL; CONVERGENCE; WIENER; ALGORITHM;

D O I：

10.1016/j.automatica.2009.09.009

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 weighted least squares (WL-S) based adaptive tracker is designed for a cl ass of Hammerstein systems. It is p roved that the tracking error is asymptotically minimized. Incorporating with the diminishing excitation technique, the minimality of the tracking error and strong consistency of the estimates for parameters of the system are simultaneously achieved. Numerical examples are given and the simulation results are consistent with the theoretical analysis. (C) 2009 Elsevier Ltd. All rights reserved.

引用

页码：2773 / 2783

页数：11

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