  This paper introduces a landing guidance strategy for reusable launch
vehicles (RLVs) using a model predictive approach based on sequential convex
programming (SCP). The proposed approach devises two distinct optimal control
problems (OCPs): planning a fuel-optimal landing trajectory that accommodates
practical path constraints specific to RLVs, and determining real-time optimal
tracking commands. This dual optimization strategy allows for reduced
computational load through adjustable prediction horizon lengths in the
tracking task, achieving near closed-loop performance. Enhancements in model
fidelity for the tracking task are achieved through an alternative rotational
dynamics representation, enabling a more stable numerical solution of the OCP
and accounting for vehicle transient dynamics. Furthermore, modifications of
aerodynamic force in both planning and tracking phases are proposed, tailored
for thrust-vector-controlled RLVs, to reduce the fidelity gap without adding
computational complexity. Extensive 6-DOF simulation experiments validate the
effectiveness and improved guidance performance of the proposed algorithm.
