Robust Spacecraft Guidance Around Small Bodies Under Uncertainty: Stochastic Optimal Control Approach

作     者：Oguri, Kenshiro McMahon, Jay W. 

作者机构：Univ Colorado Dept Aerosp Engn Sci Colorado Ctr Astrodynam Res Boulder CO 80309 USA 

出 版 物：《JOURNAL OF GUIDANCE CONTROL AND DYNAMICS》 (制导、控制和动力学杂志)

年 卷 期：2021年第44卷第7期

页      面：1295-1313页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 0804[工学-仪器科学与技术] 0825[工学-航空宇航科学与技术] 

基　　金：AM000017 

主　　题：Spacecraft Guidance Linear Quadratic Regulator Nonlinear Programming Asteroids Orbit Determination Linear Quadratic Gaussian Monte Carlo Simulation Nonlinear Dynamics Brownian Motion Computing 

摘      要：Dynamical environments around small celestial bodies are complex and uncertain, leading to highly perturbed, uncertain orbital motions in their proximity. Under such complexity and uncertainty, mission designers need to plan robust guidance and control of the spacecraft orbit to meet some requirements derived from their mission objectives such as precise science observation campaigns. To develop a robust planner for spacecraft guidance under uncertainty, this paper presents a stochastic optimal control approach to design robust guidance policies that minimize the expected control effort while ensuring the requirement satisfaction with a user-defined confidence level, i.e., chance constraints. The solution method is formulated as a two-stage optimization framework that consists of a convex programming stage, followed by a nonlinear programming stage. The developed framework is applied to a small-body global-mapping scenario on a science orbit around asteroid Bennu, demonstrating the robustness of the optimized guidance policies;the stochastic orbital states are controlled to meet science requirements to 99.9% confidence over 31 days with minimum control cost. Although the developed framework is demonstrated in a small-body global-mapping scenario, it is independent from specific equations of motion, and hence applicable to other proximity operation scenarios as well.