• DocumentCode
    258566
  • Title

    Innovative adaptive autopilot design for uninhabited surface vehicles

  • Author

    Annamalai, Andy S. K. ; Sutton, Robert ; Chenguang Yang ; Culverhouse, Phil ; Sharma, Shantanu

  • Author_Institution
    Sch. of Marine Sci. & Eng., Plymouth Univ., Plymouth, UK
  • fYear
    2013
  • fDate
    26-27 June 2013
  • Firstpage
    158
  • Lastpage
    163
  • Abstract
    In real life situations, very often a sudden change in dynamics results in missions being aborted which results in it having to be rescued before damage to other marine craft in the vicinity is caused. This problem has been suitably dealt with by an innovative adaptive autopilot design that is described herein. A model predictive control (MPC) adopts an online adaptive nature by utilizing weighted least squares (WLS). Even with random initialization, significant improvements were achieved by WLS by maintaining the intermittent continuous values of system parameters and periodically reinitializing the covariance matrix. Also, a time frame of 25 seconds appears to be the optimum to reinitialize the parameters. This novel approach enables the autopilot to cope well with significant changes in the system dynamics and empowers USVs to accomplish their desired missions.
  • Keywords
    control system synthesis; covariance matrices; least squares approximations; marine vehicles; predictive control; remotely operated vehicles; MPC; USV; WLS; adaptive autopilot design; covariance matrix; marine craft; model predictive control; random initialization; uninhabited surface vehicles; weighted least squares; Uninhabited surface vehicles; model predictive control; variable payload;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Irish Signals & Systems Conference 2014 and 2014 China-Ireland International Conference on Information and Communications Technologies (ISSC 2014/CIICT 2014). 25th IET
  • Conference_Location
    Limerick
  • Type

    conf

  • DOI
    10.1049/cp.2014.0677
  • Filename
    6912748