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Identification of ship steering dynamics based on ACA-SVR

  • Sheng Liu*
  • , Jia Song
  • , Bing Li
  • , Gao Yun Li
  • *Corresponding author for this work
  • Harbin Engineering University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

According to the high-order nonlinearity and parameter uncertainty of the ship steering dynamics, it is difficult to establish the accurate mathematical model by using normal identification methods. To solve this problem, a new kind of Support Vector Regression based on the Ant Colony Algorithm (ACA-SVR) is proposed. This method can select the parameters of SVR automatically without trial and error, thus ensure the accuracy of parameters optimization. Applying this method in the model identification of the ship steering dynamics, and comparing the identification effect with the experimental reference data. The SVR obtained by this method is able to establish the system model effectively, the structure is simple and generalization ability is well.

Original languageEnglish
Title of host publicationProceedings of 2008 IEEE International Conference on Mechatronics and Automation, ICMA 2008
Pages514-519
Number of pages6
DOIs
StatePublished - 2008
Externally publishedYes
Event2008 IEEE International Conference on Mechatronics and Automation, ICMA 2008 - Takamatsu, Japan
Duration: 5 Aug 20088 Aug 2008

Publication series

NameProceedings of 2008 IEEE International Conference on Mechatronics and Automation, ICMA 2008

Conference

Conference2008 IEEE International Conference on Mechatronics and Automation, ICMA 2008
Country/TerritoryJapan
CityTakamatsu
Period5/08/088/08/08

Keywords

  • Ant Colony Algorithm
  • Nonlinear System Identification
  • Ship Maneuvering
  • Support Vector Regression

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