Abstract This paper proposes a method that plans energy-optimal trajectories for multi-satellite formation reconfiguration in deep space environment. A novel co-evolutionary particle swarm optimization algorithm is stated to solve the nonlinear programming problem, so that the computational complexity of calculating the gradient information could be avoided. One swarm represents one satellite, and through communication with other swarms during the evolution, collisions between satellites can be avoided. In addition, a dynamic depth first search algorithm is proposed to solve the redundant search problem of a co-evolutionary particle swarm optimization method, with which the computation time can be shorten a lot. In order to make the actual trajectories optimal and collision-free with disturbance, a re-planning strategy is deduced for formation reconfiguration maneuver.

    Highlights We propose the CPSO method to solve satellite formation reconfiguration problem. We employ a D-DFS algorithm to solve the redundant search problem. We deduce a real-time re-planning strategy during reconfiguration maneuvering.


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    Title :

    Optimal satellite formation reconfiguration using co-evolutionary particle swarm optimization in deep space


    Contributors:

    Published in:

    Acta Astronautica ; 113 ; 149-163


    Publication date :

    2015-04-06


    Size :

    15 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English