An On-line Learning Algorithm for RBF Networks and its Application to Ship Inverse Control

被引：1

作者：

Bi, Gexin ^{[1
]}

Dong, Fang ^{[1
]}

机构：

[1] Dalian Maritime Univ, Coll Navigat, Dalian 116026, Peoples R China

来源：

PROCEEDINGS OF THE 2008 INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND DESIGN, VOL 1 | 2008年

关键词：

NEURAL-NETWORKS;

D O I：

10.1109/ISCID.2008.149

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：327 / 330

页数：4

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