DocumentCode
2021175
Title
An On-line Learning Algorithm for RBF Networks and its Application to Ship Inverse Control
Author
Bi, Gexian ; Dong, Fana
Author_Institution
Coll. of Navig., Dalian Maritime Univ., Dalian
Volume
1
fYear
2008
fDate
17-18 Oct. 2008
Firstpage
327
Lastpage
330
Abstract
An on-line learning algorithm is introduced referred to as dynamic orthogonal structure adaptation (DOSA) algorithm for constructing radial basis function (RBF) networks with variable network structure. The RBF network is on-line adapted for both network structure and connecting parameters. Based on DOSA algorithm, an inverse control strategy is proposed and applied to ship control. Simulation results of ship course control experiment demonstrate the applicability and effectiveness of the proposed inverse control strategy.
Keywords
learning (artificial intelligence); navigation; radial basis function networks; ships; RBF Networks; dynamic orthogonal structure adaptation; inverse control; on-line learning algorithm; radial basis function networks; Computational intelligence; Marine vehicles; Radial basis function networks; Radial basis function network; inverse control; system identification;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Design, 2008. ISCID '08. International Symposium on
Conference_Location
Wuhan
Print_ISBN
978-0-7695-3311-7
Type
conf
DOI
10.1109/ISCID.2008.149
Filename
4725619
Link To Document