Autotuned Primal–Dual Successive Convexification for Reentry Guidance

What is it about?

This work presents auto-tuned primal-dual successive convexification, an algorithm for optimizing hypersonic reentry trajectories reliably. The contribution of this work is to propose an enhanced algorithm within the sequential convex programming framework that can solve highly nonconvex problems consistently with reduced sensitivity to changes in mission parameters.

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