Gradient Based Estimation Methods for a Class of Nonlinear Systems with Colored Noises

被引:0
作者
Wang, Dongqing [1 ]
Ding, Feng [2 ]
机构
[1] Jiangnan Univ, Qingdao Univ, Coll Automat Engn, Qingdao 266071, Peoples R China
[2] Jiangnan Univ, Control Sci & Engn Res Ctr, Wuxi 214122, Peoples R China
来源
2008 IEEE INTERNATIONAL CONFERENCE ON AUTOMATION AND LOGISTICS, VOLS 1-6 | 2008年
关键词
Parameter estimation; stochastic gradient; convergence performance; forgetting factor; Hammerstein-Wiener systems;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper develops an extended stochastic estimation method to identify the parameters of Hammerstein-Wiener nonlinear models with colored noises. By replacing the unmeasurable noise terms in the information vectors of the pseudo-linear regression model with their estimates, the noise estimates can be computed by the obtained parameter estimates. The obtained parameter estimates of the identification model include the products of the original system parameters, two methods of separating the parameter estimates into original parameters are discussed: the average method and the singular value decomposition method. To improve the identification accuracy, an extended stochastic gradient algorithm with a forgetting factor is given. The simulation examples indicate that the introduction of the forgetting factor can improve the estimation accuracy.
引用
收藏
页码:736 / +
页数:2
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