This paper proposes real-time sequential convex programming (RTSCP), a method for solving a sequence of nonlinear optimization problems depending on an online parameter. We provide a contraction estimate for the proposed method and, as a byproduct, a new proof of the local convergence of sequential convex programming. The approach is illustrated by an example where RTSCP is applied to nonlinear model predictive control.
@article{arxiv.1105.3427,
title = {Real-Time Sequential Convex Programming for Optimal Control Applications},
author = {Tran Dinh Quoc and Carlo Savorgnan and Moritz Diehl},
journal= {arXiv preprint arXiv:1105.3427},
year = {2015}
}