• DocumentCode
    3473807
  • Title

    Modelling of Large Ship Motion and Design of Intelligent Rudder Control Mechanism

  • Author

    Wang, Yuanhui ; Shi, Xiaocheng ; Xia, Guoqing ; Bian, Xinqian

  • Author_Institution
    Harbin Eng. Univ.(HEU), Harbin
  • fYear
    2007
  • fDate
    18-21 Aug. 2007
  • Firstpage
    1699
  • Lastpage
    1703
  • Abstract
    A large ship is hard to keep and change its heading because of its large tonnage, large inertia, poor brake perfomance and poor tracing ability. According to the movement characteristic of large ship and the disturbance characteristic of the sea environment, three degree of freedom motion nonlinear mathematic model of large ship is established and a rudder control mechanism based Artificial Neural Network (ANN) algorithm is designed for the large ship for the first time. The paper describes how to use neural network model to keep the large ship in good state under changing sea environment and presents the approach of the feed forward neural network theory and Back Propagation Learning Algorithm (BP). The simulation results show that the ship motion mathematic model has good turning movement characteristic and the ship has good heading- change and heading-keeping characteristics under environment disturbances.
  • Keywords
    backpropagation; feedforward neural nets; intelligent control; marine engineering; motion control; nonlinear control systems; ships; artificial neural network; back propagation learning algorithm; feed forward neural network theory; intelligent rudder control mechanism; large ship motion modelling; nonlinear mathematic model; sea environment; Algorithm design and analysis; Artificial neural networks; Feedforward neural networks; Feeds; Intelligent control; Marine vehicles; Mathematical model; Mathematics; Motion control; Neural networks; Artificial Neural Network; Large ship motion model; Rudder control mechanism;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Automation and Logistics, 2007 IEEE International Conference on
  • Conference_Location
    Jinan
  • Print_ISBN
    978-1-4244-1531-1
  • Type

    conf

  • DOI
    10.1109/ICAL.2007.4338846
  • Filename
    4338846