The poor maneuverability of low lift-to-drag ratio (L/D) vehicles results in low precision of reference-trajectory guidance and difficulty in meeting load constraints. This paper presents an automatic load relief numerical predictor-corrector method for the guidance of low L/D vehicles return from low Erath orbit. By elaborately designing a bank-angle profile in each guidance circle and selecting appropriate iteration parameters, the goal of automatic load relief is achieved, which greatly reduces the maximum peak load. With the use of coupled guidance and landing error feedback algorithms, the guidance precision is improved. Aerodynamic coefficients of the vehicle and landing errors are filtered to further increase the robustness of the algorithm. Extensive Monte Carlo simulations are conducted to evaluate and verify the design features of the algorithm. The test results show that the algorithm consistently offers very satisfactory performance even in highly dispersed cases. Such an algorithm holds distinct potential for onboard applications.


    Zugriff

    Zugriff über TIB

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Automatic load relief numerical predictor-corrector guidance for low L/D vehicles return from low Earth orbit


    Beteiligte:


    Erscheinungsdatum :

    2015




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Print


    Sprache :

    Englisch



    Klassifikation :

    BKL:    55.50 Luftfahrzeugtechnik / 55.60 Raumfahrttechnik
    Lokalklassifikation TIB:    275/7040




    Predictor-corrector entry guidance for reusable launch vehicles

    Chowdhry, Rajiv / Zimmermann, Curtis / Youssef, Hussein et al. | AIAA | 2001


    Stochastic Predictor-Corrector Guidance

    McMahon, Jay W. / Amato, Davide / Kuettel, Donald et al. | TIBKAT | 2022


    Stochastic Predictor-Corrector Guidance

    McMahon, Jay W. / Amato, Davide / Kuettel, Donald et al. | AIAA | 2022


    Stochastic Predictor-Corrector Guidance

    McMahon, Jay W. / Amato, Davide / Kuettel, Donald et al. | TIBKAT | 2022