• DocumentCode
    1566815
  • Title

    SA-RL Algorithm Based Ship Steering Controller

  • Author

    Ye, Guang ; Guo, Chen

  • Author_Institution
    Autom. & Elec. Eng. Coll., Dalian Maritime Univ.
  • Volume
    3
  • fYear
    2005
  • Firstpage
    1780
  • Lastpage
    1785
  • Abstract
    Based on simulated annealing (SA) and reinforcement learning (RL) algorithm, a hybrid intelligent controller is proposed to ship steering. The SA algorithm is a powerful way to solve hard combinatorial optimization problems, which is used to adjust the parameters of the controller in this paper. The RL algorithm shows its particular superiority in ship steering, which just needs simple fuzzy information. With the advantages of the two algorithms, the controller can overcome the influence of the wind, wave and flow, the limitation that data are not exactly accurate. At last, the results of the simulation show that the ship course can be properly controlled when changeable wind, wave, and measure error exists
  • Keywords
    combinatorial mathematics; fuzzy control; intelligent control; learning (artificial intelligence); ships; simulated annealing; steering systems; hard combinatorial optimization problem; hybrid intelligent control; reinforcement learning; ship steering control; simulated annealing; Automatic control; Automation; Computer networks; Educational institutions; Fuzzy systems; Inference algorithms; Learning; Marine vehicles; Neural networks; Simulated annealing; Reinforcement Learning; Ship Steering Control; Simulated Annealing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks and Brain, 2005. ICNN&B '05. International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    0-7803-9422-4
  • Type

    conf

  • DOI
    10.1109/ICNNB.2005.1614972
  • Filename
    1614972