Iterative parameter identification methods for nonlinear functions

被引：59
|
作者：
Li, Junhong [1 ,2 ]
Ding, Ruifeng [1 ]
Yang, Yi [2 ]
机构：
[1] Jiangnan Univ, Sch Internet Things Engn, Wuxi 214122, Peoples R China
[2] Nantong Univ, Sch Elect Engn, Nantong 226019, Peoples R China
来源：
APPLIED MATHEMATICAL MODELLING | 2012年 / 36卷 / 06期
关键词：
System modelling; Nonlinear systems; Parameter estimation; Gradient iteration; Newton iteration; SYLVESTER MATRIX EQUATIONS; SELF-TUNING CONTROL; HIERARCHICAL IDENTIFICATION; ESTIMATION ALGORITHM; SYSTEMS;
D O I：
10.1016/j.apm.2011.09.057
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
This paper considers identification problems of nonlinear functions fitting or nonlinear systems modelling. A gradient based iterative algorithm and a Newton iterative algorithm are presented to determine the parameters of a nonlinear system by using the negative gradient search method and Newton method. Furthermore, two model transformation based iterative methods are proposed in order to enhance computational efficiencies. By means of the model transformation, a simpler nonlinear model is achieved to simplify the computation. Finally, the proposed approaches are analyzed using a numerical example. (C) 2011 Elsevier Inc. All rights reserved.
引用
收藏
页码：2739 / 2750
页数：12
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