Real-time Discrete Nonlinear Identification via Recurrent High Order Neural Networks

被引：0
|
作者：
Alanis, Alma Y. [1 ]
Sanchez, Edgar N. [2 ]
Loukianov, Alexander G. [2 ]
机构：
[1] Univ Guadalajara, CUCEI, Apartado Postal 51-71,Col Las Aguilas, Zapopan 45080, Jalisco, Mexico
[2] CINVESTAV, Unidad Guadalajara, Guadalajara 45091, Jalisco, Mexico
来源：
COMPUTACION Y SISTEMAS | 2010年 / 14卷 / 01期
关键词：
Neural identification; Extended Kalman filtering learning; Discrete-time nonlinear systems; Three phase induction motor;
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 deals with the discrete-time nonlinear system identification via Recurrent High Order Neural Networks, trained with an extended Kalman filter (EKF) based algorithm. The paper also includes the respective stability analysis on the basis of the Lyapunov approach for the whole scheme. Applicability of the scheme is illustrated via real-time implementation for a three phase induction motor.
引用
收藏
页码：63 / 72
页数：10
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