Identification of Wiener, Hammerstein, and NARX systems as Markov Chains with improved estimates for their nonlinearities

被引：16
作者：
Zhao, Wenxiao
Chen, Han-Fu
机构：
[1] Chinese Acad Sci, Acad Math & Syst Sci, Key Lab Syst & Control, Beijing 100190, Peoples R China
[2] Chinese Acad Sci, Natl Ctr Math & Interdisciplinary Sci, Beijing 100190, Peoples R China
来源：
SYSTEMS & CONTROL LETTERS | 2012年 / 61卷 / 12期
关键词：
Wiener system; Hammerstein system; Nonlinear ARX system; Markov chain; Recursive identification; Stochastic approximation; Derivative estimation; RECURSIVE-IDENTIFICATION; MODEL; CONVERGENCE; ALGORITHMS; MEMORY; SERIES;
D O I：
10.1016/j.sysconle.2012.08.008
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The Wiener, Hammerstein, and nonlinear ARX systems are identified not only for their linear subsystems (if they exist) but also for the nonlinearities with their first derivatives. It is assumed that the input signals and noises are mutually independent and both are sequences of independent and identically distributed (lid) random variables. The estimates based on the stochastic approximation algorithms with expanding truncations (SAAWET) are proved to be strongly consistent with the help of the Markov properties possessed by these systems. The estimates of the first derivatives improve the accuracy of interpolating the nonlinearity curves as validated by simulation examples. (C) 2012 Elsevier B.V. All rights reserved.
引用
收藏
页码：1175 / 1186
页数：12
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