Parameter Identification Methods for an Additive Nonlinear System

被引：0
|
作者：
Jing Chen
Yunxia Ni
机构：
[1] Wuxi Professional College of Science and Technology,
来源：
Circuits, Systems, and Signal Processing | 2014年 / 33卷
关键词：
Parameter estimation; Stochastic gradient; Recursive least squares; Preload nonlinearity; Piece-wise nonlinearity; Additive system;
D O I：
暂无
中图分类号：
学科分类号：
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
收藏
页码：3053 / 3064
页数：11
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