Accumulative Learning using Multiple ANN for Flexible Link Control

Author

de Almeida Neto, Areolino ; Góes, Lúis Carlos Sandoval ; Nascimento, Cairo LÙcio, Jr.

Author_Institution

Eng. de Eletricidade, Fed. Univ. of Maranhao, Maranhao, Brazil

Volume

46

Issue

2

fYear

2010

fDate

4/1/2010 12:00:00 AM

Firstpage

508

Lastpage

524

Abstract

This paper presents a scheme of multiple neural networks (MNNs) with a new strategy of combination. This combination can obtain an accumulative learning: the knowledge is increased by gradually adding more neural networks to the system. This scheme is applied to flexible link control via feedback-error-learning (FEL) strategy, here called multi-network-feedback-error-learning. Three different neural control approaches are used to control a flexible link, and it is shown that a better inverse dynamic model of the plant is obtained in this case.

Keywords

couplings; flexible structures; learning systems; neurocontrollers; state feedback; accumulative learning; feedback error learning strategy; flexible link control; inverse dynamic model; multinetwork feedback error learning; multiple ANN; multiple neural networks; Aerodynamics; Artificial neural networks; Control nonlinearities; Control systems; Error correction; Inverse problems; Neural networks; Nonlinear control systems; Nonlinear dynamical systems; Space technology;

fLanguage

English

Journal_Title

Aerospace and Electronic Systems, IEEE Transactions on

Publisher

ieee

ISSN

0018-9251

Type

jour

DOI

10.1109/TAES.2010.5461638

Filename

5461638