Abstract This research investigates the performance of bi-level hybrid optimal control algorithms in the solution of minimum delta-velocity geostationary transfer maneuvers with cooperative en-route inspection. The maneuvers, introduced here for the first time, are designed to populate a geostationary constellation of space situational awareness satellites while providing additional characterization of objects in lower-altitude orbit regimes. The maneuvering satellite, called the chaser, performs a transfer from low Earth orbit to geostationary orbit, during which it performs an inspection of one of several orbiting targets in conjunction with a ground site for the duration of the target׳s line-of-site contact with that site. A three-target scenario is used to test the performance of multiple bi-level hybrid optimal control algorithms. A bi-level hybrid algorithm is then utilized to solve fifteen-, and thirty-target scenarios and shown to have increasing benefit to complete enumeration as the number of targets is increased. Results indicate that the en-route inspection can be accomplished for a small increase in the delta-velocity required for a simple transfer to geostationary orbit given the same initial conditions.

    Highlights We define the Geostationary Transfer Maneuver with En-Route Inspection (GTMEI). We compare hybrid optimal control (HOC) algorithms in the solution of a three-target GTMEI. Employing an infeasible cutoff provides near-optimal results with much less computational time. A bi-level HOC algorithm is used to solve fifteen- and thirty-target GTMEIs. GTMEI requires the addition of only a small fraction of the ΔV required for a GEO transfer.


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    Title :

    Near-optimal geostationary transfer maneuvers with cooperative en-route inspection using hybrid optimal control


    Contributors:

    Published in:

    Acta Astronautica ; 105 , 2 ; 395-406


    Publication date :

    2014-09-22


    Size :

    12 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English





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