Parameter Identification Methods for an Additive Nonlinear System

被引：16

作者：

Chen, Jing ^{[1
]}

Ni, Yunxia ^{[1
]}

机构：

[1] Wuxi Profess Coll Sci & Technol, Wuxi 214028, Peoples R China

来源：

CIRCUITS SYSTEMS AND SIGNAL PROCESSING | 2014年 / 33卷 / 10期

基金：

中国国家自然科学基金;

关键词：

Parameter estimation; Stochastic gradient; Recursive least squares; Preload nonlinearity; Piece-wise nonlinearity; Additive system; LEAST-SQUARES ALGORITHM; WIENER SYSTEMS; MODEL; STATE;

D O I：

10.1007/s00034-014-9793-6

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper deals with parameter identification methods for an additive nonlinear system with a preload nonlinearity and a piece-wise nonlinearity. By using a switching function, we transfer the model of the additive nonlinear system into an identification model, and propose a recursive least squares algorithm and two modified stochastic gradient (SG) algorithms to estimate the parameters of the identification model. The simulation results indicate that the proposed methods converge faster than the SG algorithm.

引用

页码：3053 / 3064

页数：12

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