This paper presents a novel method for expanding the use of sequential convex programming (SCP) to the domain of optimal guidance and control problems with nonlinear dynamics constraints. SCP is a useful tool in obtaining real-time solutions to direct optimal control, but it is unable to adequately model nonlinear dynamics due to the linearization and discretization required. As nonlinear program solvers are not yet functioning in real-time, a tool is needed to bridge the gap between satisfying the nonlinear dynamics and completing execution fast enough to be useful. Two methods are proposed, SCP with nonlinear dynamics correction (SCPn) and modified SCPn (M-SCPn), which mixes SCP and SCPn to reduce runtime and improve algorithmic robustness. Both methods are proven to generate optimal state and control trajectories that satisfy the nonlinear dynamics. Simulations are presented to validate the efficacy of the methods as compared with SCP.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Optimal Guidance and Control with Nonlinear Dynamics Using Sequential Convex Programming


    Contributors:

    Published in:

    Publication date :

    2020-04-01




    Type of media :

    Conference paper , Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




    Solving Optimal Control with Nonlinear Dynamics Using Sequential Convex Programming

    Foust, Rebecca / Chung, Soon-Jo / Hadaegh, Fred Y. | AIAA | 2019



    Autonomous Descent Guidance via Sequential Pseudospectral Convex Programming

    Sagliano, Marco / Seelbinder, David / Theil, Stephan | Springer Verlag | 2023

    Free access

    BEZIER-BASED SEQUENTIAL CONVEX PROGRAMMING METHOD FOR LAUNCH ASCENT GUIDANCE

    Zhao, Mengxin / Pan, Binfeng / Li, Mingxiang | TIBKAT | 2021