This paper presents trajectory planning algorithms for large-scale satellite clusters reconfiguration based on sequential convex programming, and these algorithms consider fuel consumption and collision avoidance. Firstly, the trajectory planning problem is formulated as a nonconvex optimal control problem with nonlinear dynamics and nonconvex path constraints. Secondly, the original nonlinear continuous optimal control problem is transformed into a discrete convex optimization subproblem through linearization and discretization. Collision avoidance strategy between discrete points and obstacle avoidance constraints are considered in the convex subproblem to ensure that the trajectories are collision-free. Thirdly, coupled and decoupled sequential convex programming methods are proposed for rapidly generating collision-free and fuel-efficient trajectories. Finally, comparative numerical simulations are presented to demonstrate that as the number of satellites increases, 94 to 99 percent performance improvement over the pseudo-spectral method is achieved in terms of computational efficiency.

本文提出了基于序列凸规划的大规模卫星集群重构轨迹规划算法，这些算法考虑了燃料消耗和避免碰撞。首先，轨迹规划问题被表述为具有非线性动力学和非凸路径约束的非凸最优控制问题。其次，将原来的非线性连续最优控制问题通过线性化和离散化转化为离散的凸优化子问题。在凸子问题中考虑了离散点之间的避障策略和避障约束，以确保轨迹无碰撞。第三，提出了耦合和解耦的顺序凸规划方法，用于快速生成无碰撞和省油的轨迹。最后，比较数值模拟表明，随着卫星数量的增加，在计算效率方面比伪谱方法提高了 94% 到 99% 的性能。