  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.
