A Convex Optimization Approach for Finite-Thrust Time-Constrained Cooperative Rendezvous

Abstract

This paper presents a convex approach to the optimization of a cooperative rendezvous, that is, the problem of two distant spacecraft that simultaneously operate to get closer. Convex programming guarantees convergence towards the optimal solution in a limited, short, time by using highly efficient numerical algorithms. A combination of lossless and successive convexification techniques is adopted to handle the nonconvexities of the original problem. Specifically, a convenient change of variables and a constraint relaxation are performed, while a successive linearization of the equations of motion is employed to handle the nonlinear dynamics. A filtering technique concerning the recursive update of the reference solution is proposed in order to enhance the algorithm robustness. Numerical results are presented and compared with those provided by an indirect method.

Advances in Trajectory Optimization for Space Vehicle Control

“…(Lu and Liu, 2013;Liu and Lu, 2014) showed that fast and reliable trajectory optimization is still possible in this case, by applying the same lossless convexification as in Problem 63 to the constraints (65c) and (65d) and successively linearizing the dynamics (65b). (Benedikter et al, 2019b) further proposed a filtering technique for updating the linearization reference point to improve the algorithm robustness. The advantage of this approach is its compatibility with general Keplerian orbits and perturbations like J 2 harmonic and aerodynamic drag.…”