Discrete-time neural identifier for electrically driven nonholonomic mobile robots

Author

Alanis, Alma Y. ; Lopez-Franco, Michel ; Arana-Daniel, Nancy ; Lopez-Franco, Carlos

Author_Institution

CUCEI, Univ. de Guadalajara, Zapopan, Mexico

fYear

2011

fDate

July 31 2011-Aug. 5 2011

Firstpage

1067

Lastpage

1073

Abstract

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.

Keywords

Kalman filters; discrete time systems; electric drives; learning (artificial intelligence); mobile robots; neurocontrollers; nonlinear control systems; recurrent neural nets; uncertain systems; EKF-based algorithm; RHONN training; discrete time recurrent high order neural network; discrete time unknown nonlinear system; electrically driven nonholonomic mobile robot; extended Kalman filter; external uncertainty; internal uncertainty; nonlinear discrete time neural identifier; Biological neural networks; Kalman filters; Mathematical model; Mobile robots; Nonlinear systems; Training; Wheels; Kalman Filtering; Neural Identification; Nonholonomic mobile robot; Prediction; Recurrent Neural Networks;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks (IJCNN), The 2011 International Joint Conference on

Conference_Location

San Jose, CA

ISSN

2161-4393

Print_ISBN

978-1-4244-9635-8

Type

conf

DOI

10.1109/IJCNN.2011.6033341

Filename

6033341