• DocumentCode
    434630
  • Title

    Neural network model reference adaptive control of a surface vessel

  • Author

    Leonessa, Alexander ; VanZwieten, Tannen S.

  • Author_Institution
    Fac. of Mechanical, Mater., & Aerosp. Eng., Central Florida Univ., Orlando, FL, USA
  • Volume
    1
  • fYear
    2004
  • fDate
    17-17 Dec. 2004
  • Firstpage
    662
  • Abstract
    A neural network model reference adaptive the desired trajectory for dynamics of a particular, known controller for trajectory tracking of nonlinear systems is structure. The results were verified through simulation using developed. The proposed control algorithm uses a single layer neural network that bypasses the need for information about the system´s dynamic structure and provides portability. Numerical simulations are performed using a three-degree of freedom nonlinear dynamic model of a surface vessel. The results demonstrate the controller performance in terms of tuning, robustness and tracking.
  • Keywords
    hovercraft; model reference adaptive control systems; neurocontrollers; nonlinear control systems; remotely operated vehicles; model reference adaptive control; neural network; nonlinear dynamic model; nonlinear systems; surface vessel; Adaptive control; Adaptive systems; Control systems; Neural networks; Nonlinear control systems; Nonlinear systems; Numerical simulation; Programmable control; Robust control; Trajectory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control, 2004. CDC. 43rd IEEE Conference on
  • Conference_Location
    Nassau
  • ISSN
    0191-2216
  • Print_ISBN
    0-7803-8682-5
  • Type

    conf

  • DOI
    10.1109/CDC.2004.1428720
  • Filename
    1428720