For the next generation of NASA’s missions, explicit, path-adaptive descent guidance algorithms must provide the stability and customizability required for a safe and efficient descent to the lunar surface, while also meeting program and vehicle constraints. Several descent algorithms have been flown and tested for single-stage landers through the Apollo and Altair programs, but thus far little analysis has been conducted involving the application of these algorithms to a two-stage descent vehicle. Due to payload mass and fairing constraints of the existing fleet of launch vehicles, multi-stage descent architectures are a unique option for achieving the greatest possible mass to lunar surface. This paper seeks to compare the performance of guidance configurations of a lunar lander system consisting of two stages, one of which separates partway through descent. Through development of this paper, an optimization suite has been written that is specifically designed for optimizing planetary non-atmospheric two-stage descent trajectories, and is used as a baseline to compare the guidance algorithms tested. Time-to-go computational methods and ignition logic routines that may be employed in a lunar environment are also discussed. Preliminary results are presented that show relative performance metrics for a range of different guidance algorithm configurations.


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    Titel :

    Path-Adaptive Guidance Algorithm Trades for a Two-Stage Lunar Descent Vehicle


    Beteiligte:
    Jason M Everett (Autor:in) / Anand R Iyer (Autor:in)

    Kongress:

    43rd Annual AAS Guidance, Navigation & Controls Conference ; 2020 ; Breckenridge, CO, US


    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Keine Angabe


    Sprache :

    Englisch