• DocumentCode
    424687
  • Title

    Model predictive control based trajectory optimization for nap-of-the-earth (NOE) flight including obstacle avoidance

  • Author

    Lapp, Tiffany ; Singh, Leena

  • Author_Institution
    Massachusetts Inst. of Technol., USA
  • Volume
    1
  • fYear
    2004
  • fDate
    June 30 2004-July 2 2004
  • Firstpage
    891
  • Abstract
    This work presents a model predictive control based trajectory optimization method for nap-of-the-earth (NOE) flight including obstacle avoidance, emphasizing the mission objective of low altitude at high speed. A NOE trajectory reference is generated over a subspace of the terrain. It is then inserted into the cost function and the resulting trajectory tracking error term is weighted for more precise longitudinal tracking than lateral tracking through the introduction of the TF/TA ratio. Obstacle avoidance including preclusion of ground collision is accomplished through the establishment of hard state constraints. These state constraints create a ´safe envelope´ within which the optimal trajectory can be found. Steps are taken to reduce complexity in the optimization problem including perturbational linearization in the prediction model generation and the use of control basis functions. Preliminary results over a variety of sample terrains are provided to show the mission objective of low altitude and high speed was met satisfactorily without terrain or obstacle collision, however, methods to preclude or deal with infeasibility must be investigated as speed is increased to and past 30 knots.
  • Keywords
    aerospace control; collision avoidance; linearisation techniques; optimisation; perturbation techniques; predictive control; control basis function; ground collision; model predictive control; nap-of-the-earth flight; obstacle avoidance; perturbational linearization; trajectory optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference, 2004. Proceedings of the 2004
  • Conference_Location
    Boston, MA, USA
  • ISSN
    0743-1619
  • Print_ISBN
    0-7803-8335-4
  • Type

    conf

  • Filename
    1383719