A Sequential Learning Algorithm for RBF Networks with Application to Ship Inverse Control

  • Gexin Bi
  • Fang Dong
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5263)

Abstract

A sequential learning algorithm for constructing radial basis function (RBF) network is introduced referred to as dynamic orthogonal structure adaptation (DOSA) algorithm. The algorithm learns samples sequentially, with both structure and connecting parameters of network are adjusted on-line. The algorithm is further improved by setting initial hidden units and incorporating weight factors. Based on the improved DOSA algorithm, a direct inverse control strategy is introduced and applied to ship control. Simulation results of ship course control simulation demonstrate the applicability and effectiveness of the improved DOSA algorithm and the RBF network-based inverse control strategy.

Keywords

Radial basis function network Sequential learning Inverse control 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Gexin Bi
    • 1
  • Fang Dong
    • 1
  1. 1.College of NavigationDalian Maritime UniversityDalianChina

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