• DocumentCode
    1935274
  • Title

    Optimal merging of multiple aircrafts to waypoints via controlled time of arrival windows

  • Author

    Poolla, Chaitanya ; Ishihara, A.K.

  • Author_Institution
    Electr. & Comput. Eng., Carnegie Mellon SV, Moffett Field, CA, USA
  • fYear
    2013
  • fDate
    2-9 March 2013
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    This paper presents an algorithm that computes the optimal arrival times and velocities required for maximizing worst case mutual separation in a multiple aircraft optimal merging scenario. The approach leverages the Pontryagin Maximum Principle (PMP) to rapidly generate locally optimal trajectories per aircraft and an outer-loop Particle Swarm Optimization (PSO) scheme to search for globally optimal merging dynamics. The subset of feasible Controlled Time of Arrival (CTA) and velocity windows is estimated based on an asymptotic approximation of the locally optimal trajectory generated by the PMP. The Particle Swarm Optimization (PSO) scheme maximizes the minimum separation between all aircrafts over all instances of the trajectory. The cost functional has been chosen to minimize load factor (enhance comfort) and maximize worst case mutual separation (improve safety). Simulations based on a simplified lateral aircraft model subject to bounded control inputs are provided to illustrate the concept.
  • Keywords
    aircraft control; optimal control; particle swarm optimisation; CTA; PMP; PSO scheme; asymptotic approximation; controlled time of arrival windows; globally optimal merging dynamics; locally optimal trajectories per aircraft; locally optimal trajectory; multiple aircraft optimal merging scenario; outer-loop PSO scheme; outer-loop particle swarm optimization scheme; particle swarm optimization scheme; pontryagin maximum principle; simplified lateral aircraft model; Aircraft; Merging; ATC automation; CTAs; NextGen FMS; Optimal Lateral Trajectory; Separation assurance;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Aerospace Conference, 2013 IEEE
  • Conference_Location
    Big Sky, MT
  • ISSN
    1095-323X
  • Print_ISBN
    978-1-4673-1812-9
  • Type

    conf

  • DOI
    10.1109/AERO.2013.6496934
  • Filename
    6496934