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Published April 2020 | Submitted
Journal Article Open

Optimal Guidance and Control with Nonlinear Dynamics Using Sequential Convex Programming

Abstract

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, sequential convex programming 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 to SCP.

Additional Information

© 2019 American Institute of Aeronautics and Astronautics. The work of Rebecca Foust was supported by a NASA Space Technology Research Fellowship (grant # NNX15AP48H), in part at the Jet Propulsion Laboratory (JPL). Government sponsorship is acknowledged. The authors thank Kyunam Kim, Amir Rahmani, Rob Fuentes, Richard Choroszucha, and Christian Chilan for their technical input.

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August 19, 2023
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