In this article, an adaptive sequential convex programming (SCP) is presented for rapid ascent trajectory optimization of Mars ascent vehicle with multiple flight phases. A modified Chebyshev–Picard iteration algorithm with error feedback integral quasi-linearization in the form of a second-order system is used to deal with the dynamic hard constraints in the optimal control problem, so as to improve the convergence performance of the SCP. Then, the adaptive trust-region strategy and the adaptive node number strategy are combined to further improve the computational speed in the case of undesirable initial guess. Numerical simulations of the Mars ascent problem are given to show that this method has superior performance in terms of convergence and computational time compared to existing optimization methods.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Adaptive Sequential Convex Programming for Mars Ascent Vehicle Multiphase Trajectory Optimization


    Contributors:
    Li, Kun (author) / Guo, Yanning (author) / Ran, Guangtao (author) / Park, Ju H. (author)


    Publication date :

    2024-12-01


    Size :

    1598565 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Rapid ascent trajectory optimization for guided rockets via sequential convex programming

    Zhang, Kai / Yang, Shuxing / Xiong, Fenfen | SAGE Publications | 2019




    TRAJECTORY OPTIMIZATION FOR A MARS ASCENT VEHICLE

    Benito, Joel / Johnson, Breanna J. | British Library Conference Proceedings | 2016


    Trajectory Optimization for a Mars Ascent Vehicle

    Benito, Joel / Johnson, Breanna | AIAA | 2016