Parameter estimation methods for nonlinear systems

被引：10

作者：

Li, Junhong ^{[1
,2
]}

Ding, Rui ^{[2
]}

机构：

[1] Nantong Univ, Sch Elect Engn, Nantong 226019, Peoples R China

[2] Jiangnan Univ, Sch Internet Things Engn, Wuxi 214122, Peoples R China

来源：

APPLIED MATHEMATICS AND COMPUTATION | 2013年 / 219卷 / 09期

关键词：

System modeling; Nonlinear systems; Parameter estimation; Gradient iteration; Newton iteration; SYLVESTER MATRIX EQUATIONS; IDENTIFICATION METHODS; ALGORITHMS;

D O I：

10.1016/j.amc.2012.09.045

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

This paper discusses parameter estimation problems of nonlinear system modeling. Two model transformation based estimation methods are proposed. The basic idea is to transform a complex nonlinear optimization problem into a linear or simple nonlinear optimization problem which is easy to solve. Then, according to the gradient search principle and the Newton method, a gradient based iterative algorithm and a Newton iterative algorithm are derived to determine the parameters of the nonlinear systems. Finally a numerical example is provided. (C) 2012 Elsevier Inc. All rights reserved.

引用

页码：4278 / 4287

页数：10

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