Identification of Hammerstein-Wiener models

被引：233

作者：

Wills, Adrian ^{[1
]}

Schon, Thomas B. ^{[2
]}

Ljung, Lennart ^{[2
]}

Ninness, Brett ^{[1
]}

机构：

[1] Univ Newcastle, Sch Elect Engn & Comp Sci, Callaghan, NSW 2308, Australia

[2] Linkoping Univ, Div Automat Control, SE-58183 Linkoping, Sweden

来源：

AUTOMATICA | 2013年 / 49卷 / 01期

基金：

澳大利亚研究理事会; 瑞典研究理事会;

关键词：

System identification; Hammerstein; Wiener; Block-oriented models; Nonlinear models; Dynamic systems; Monte Carlo method; Smoothing; Expectation maximization algorithm; Particle methods; Maximum Likelihood; MAXIMUM-LIKELIHOOD-ESTIMATION; NONLINEAR-SYSTEMS;

D O I：

10.1016/j.automatica.2012.09.018

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper develops and illustrates a new maximum-likelihood based method for the identification of Hammerstein-Wiener model structures. A central aspect is that a very general situation is considered wherein multivariable data, non-invertible Hammerstein and Wiener nonlinearities, and colored stochastic disturbances both before and after the Wiener nonlinearity are all catered for. The method developed here addresses the blind Wiener estimation problem as a special case. (C) 2012 Elsevier Ltd. All rights reserved.

引用

页码：70 / 81

页数：12

共 45 条

[1] Blind system identification [J].