Remarks on "Successive Convexification: A Superlinearly Convergent Algorithm for Non-convex Optimal Control Problems"
Optimization and Control
2024-03-15 v2
Abstract
The purpose of this note is to highlight and address inaccuracies in the convergence guarantees of SCvx, a nonconvex trajectory optimization algorithm proposed by Mao et al. (arXiv:1804.06539), and make connections to relevant prior work. Specifically, we identify errors in the convergence proof within Mao et al. (arXiv:1804.06539) and reestablish the proof of convergence by employing a new method under stricter assumptions.
Cite
@article{arxiv.2403.00733,
title = {Remarks on "Successive Convexification: A Superlinearly Convergent Algorithm for Non-convex Optimal Control Problems"},
author = {Dayou Luo and Purnanand Elango and Behcet Acikmese},
journal= {arXiv preprint arXiv:2403.00733},
year = {2024}
}