A stochastic model predictive control (SMPC) algorithm is developed to solve the problem of three-dimensional spacecraft rendezvous and docking with unbounded disturbance. In particular, we only assume that the mean and variance information of the disturbance is available. In other words, the probability density function of the disturbance distribution is not fully known. Obstacle avoidance is considered during the rendezvous phase. Line-of-sight cone, attitude control bandwidth, and thrust direction constraints are considered during the docking phase. A distributionally robust optimization based algorithm is then proposed by reformulating the SMPC problem into a convex optimization problem. Numerical examples show that the proposed method improves the existing model predictive control based strategy and the robust model predictive control based strategy in the presence of disturbance.

中文翻译：

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通过分布式鲁棒优化方法对航天器交会和对接的随机模型预测控制

提出了一种随机模型预测控制（SMPC）算法来解决三维航天器交会对接的无界扰动问题。特别是，我们只假设扰动的均值和方差信息是可用的。换言之，扰动分布的概率密度函数并不完全已知。在会合阶段考虑避障。在对接阶段考虑视距锥、姿态控制带宽和推力方向约束。然后通过将 SMPC 问题重新构造为凸优化问题，提出了一种基于分布鲁棒优化的算法。