Discrete-Time Neural Identifier for Electrically Driven Nonholonomic Mobile Robots

被引：0

作者：

Alanis, Alma Y. ^{[1
]}

Lopez-Franco, Michel ^{[1
]}

Arana-Daniel, Nancy ^{[1
]}

Lopez-Franco, Carlos ^{[1
]}

机构：

[1] Univ Guadalajara, CUCEI, Zapopan 45080, Jalisco, Mexico

来源：

2011 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN) | 2011年

关键词：

Recurrent Neural Networks; Kalman Filtering; Prediction; Neural Identification; Nonholonomic mobile robot; STATE ESTIMATION; NETWORKS; OBSERVERS; TRACKING; DESIGN;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A nonlinear discrete-time neural identifier for discrete-time unknown nonlinear systems, in presence of external and internal uncertainties are presented. This identifier is based on a discrete-time recurrent high order neural network (RHONN) trained with an extended Kalman filter (EKF)-based algorithm. Applicability of the scheme is illustrated via simulation for an electrically driven nonholonomic mobile robot.

引用

页码：1067 / 1073

页数：7

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