Koopman-Operator-Based Safe Learning Control for Spacecraft Attitude Reorientation With Angular Velocity Constraints

IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS(2023)

引用 0|浏览1
暂无评分
摘要
This article presents the design of a safe learning attitude controller, based on the Koopman operator (KO), for rest-to-rest spacecraft attitude reorientation under angular velocity constraints. Specifically, a higher-dimensional linear error attitude model is established based on the KO theory and then discretized. An explicit safe learning control strategy with safety-stabilization guarantee is then developed based on the transformed KO model. By performing a loop transformation and convexifying the safety-stabilization conditions, the safe learning controller design is further transformed into a constrained optimization problem, which is independent of the attitude states and thus can be solved offline. Finally, the trained higher-dimensional safe learning controller is mapped to the 3-D attitude controller of the original nonlinear system via the least-squares method for online implementation. In addition, the inner-approximation of the region of attraction (ROA) is provided. Comparison simulations are carried out to validate the effectiveness of the presented strategy.
更多
查看译文
关键词
Attitude control,Space vehicles,Angular velocity,Aerodynamics,Nonlinear dynamical systems,Safety,Lyapunov methods,Angular velocity constraints,attitude reorientation,Koopman operator,safe learning
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要