RRT-Based Steering Law for Singularity Avoidance of Control Moment Gyros used for Spacecraft Target Acquisition

Abhilash Mony
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引用次数: 0

Abstract

A cluster of single gimbal control moment gyroscopes (CMGs) is commonly employed on spacecraft for generating large torques, for fast in-track and cross-track maneuvers. It is well-known that the presence of singular configurations presents challenges when using CMGs for high-precision maneuvers. In this paper, we pose the problem of steering the attitude dynamics of a spacecraft in the context of robotic motion planning, and investigate the use of a Rapidly-Exploring Random Trees (RRT) algorithm for singularity avoidance. The analogy exploited in this approach is that between a singularity and a solid obstacle in the motion planning problem. We demonstrate the effectiveness of the singularity avoidance algorithm through numerical simulation of a CMG cluster on a rigid spacecraft performing target acquisition. The study compares the performance, based on the error in the torque tracking and value of the singularity index for the RRT algorithm vis-a-vis conventional steering laws.
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基于rrt的航天器目标捕获控制力矩陀螺奇异避免转向律
单万向节控制力矩陀螺仪(CMGs)集群通常用于航天器产生大扭矩,用于快速的轨道内和跨轨道机动。众所周知,当使用cmg进行高精度机动时,奇异构型的存在会带来挑战。在本文中,我们提出了机器人运动规划背景下航天器姿态动力学的控制问题,并研究了快速探索随机树(RRT)算法在奇点避免中的应用。这种方法利用的类比是运动规划问题中的奇点和固体障碍物之间的类比。通过在刚性航天器上对CMG集群进行目标捕获的数值模拟,验证了奇异避免算法的有效性。研究了基于转矩跟踪误差和奇异指标值的RRT算法与常规转向律的性能比较。
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