DYNAMICS MODELING OF FLUID-POWER SYSTEMS APPLYING A GLOBAL ERROR DESCENT ALGORITHM TO A SELF-ORGANIZING RADIAL BASIS FUNCTION NETWORK

Authors
XUE Y WATTON J
Citation
Y. Xue et J. Watton, DYNAMICS MODELING OF FLUID-POWER SYSTEMS APPLYING A GLOBAL ERROR DESCENT ALGORITHM TO A SELF-ORGANIZING RADIAL BASIS FUNCTION NETWORK, Mechatronics, 8(7), 1998, pp. 727-745
Citations number
11
Categorie Soggetti
Robotics & Automatic Control","Computer Science Artificial Intelligence","Engineering, Eletrical & Electronic","Engineering, Mechanical","Robotics & Automatic Control","Computer Science Artificial Intelligence
Journal title
Mechatronics → ACNP
ISSN journal
09574158
Volume
8
Issue
7
Year of publication
1998
Pages
727 - 745
Database
ISI
SICI code
0957-4158(1998)8:7<727:DMOFSA>2.0.ZU;2-8
Abstract
A Radial Basis Function network is a one-hidden layer feed forward typ e network, which is special for its multidimensional centre to each hi dden neuron. A key issue is how to set the hidden neurons and select t heir centres to make the network efficiently converge to the required target. A method is proposed in this study for self-organising hidden neurons and training the centres and weights by the proposed global er ror decent (GED) algorithm along with a modified genetic algorithm (GA ) and the method of least squares (LS). Its effectiveness is illustrat ed using two non-linear dynamic modelling examples of a fluid power co mponent and a system. (C) 1998 Elsevier Science Ltd. All rights reserv ed.