• DocumentCode
    1883056
  • Title

    Stochastic control for underwater optimal trajectories

  • Author

    Nègre, Adrien ; Marceau, Olivier ; Laneuville, Dann ; Zhang, Huilong ; Saporta, Benoite De ; Dufour, Francois

  • Author_Institution
    DCNS Res., Toulon, France
  • fYear
    2012
  • fDate
    3-10 March 2012
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    This paper describes an original approach based on dynamic programming theory (discrete-time finite horizon Markov control) to address the difficult problem of computing optimal trajectories with respect to some criteria for any vehicle evolving in a given environment (in a probabilistic point of view) to accomplish some tasks (defined in a complex Lipschitz criteria). After a brief remind about dynamic programming. The whole control process is detailled and applied in this paper for a submarine equipped with a sonar system which wants to detect targets as well as possible. Promising result about the optimal depth control for a submarine are presented with one and then two targets showing that the chosen approach is a good candidate.
  • Keywords
    Markov processes; discrete time systems; dynamic programming; marine engineering; optimal control; position control; sonar; stochastic systems; underwater vehicles; Lipschitz criteria; discrete-time finite horizon Markov control; dynamic programming; optimal depth control; probabilistic point-of-view; sonar system; stochastic control; submarine; underwater optimal trajectory; Aerospace electronics; Dynamic programming; Optimal control; Quantization; Stochastic processes; Trajectory; Underwater vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Aerospace Conference, 2012 IEEE
  • Conference_Location
    Big Sky, MT
  • ISSN
    1095-323X
  • Print_ISBN
    978-1-4577-0556-4
  • Type

    conf

  • DOI
    10.1109/AERO.2012.6187191
  • Filename
    6187191