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 Least Squares Support Vector Regression based on the Particle Swarm Optimization (PSO-LSSVR) is proposed. This method can select the parameters of LSSVR automatically without trial and error, thus ensure the accuracy of parameters optimization. Apply this method to the model identification of the ship steering dynamics, and compare the identification effect with the experimental reference data. The PSO-LSSVR is able to establish the system model effectively, the structure is simple and generalization ability is well.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Investigation of steering dynamics ship model identification based on PSO-LSSVR


    Contributors:
    Liu, Sheng (author) / Song, Jia (author) / Li, Bing (author) / Li, Gaoyun (author)


    Publication date :

    2008-12-01


    Size :

    607554 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Identification of ship steering dynamics

    Astroem, K.J. / Kaellstroem, C.G. | Tema Archive | 1976


    Identification of Ship Steering Dynamics Based on ACA-SVR

    Sheng, L. / Jia, S. / Bing, L. et al. | British Library Conference Proceedings | 2008


    Sensor fault diagnosis for electro-hydraulic actuator based on QPSO-LSSVR

    Ting Li / Yongping Yu / Jian Wang et al. | IEEE | 2016


    Dynamics of automatic ship steering system

    Goclowski, J. / Gelb, A. | Engineering Index Backfile | 1966


    Ship steering device and ship steering method

    HARA NAOHIRO / HAYASHI AKIYOSHI / HIROSE TOSHIMITSU | European Patent Office | 2015

    Free access