宇航学报

宇航学报 ›› 2017, Vol. 38 ›› Issue (9): 927-935.doi: 10.3873/j.issn.1000-1328.2017.09.005

• 飞行器设计与力学 • 上一篇    下一篇

大角度机动下带挠性附件航天器转动惯量在轨辨识

何骁，谭述君，吴志刚   

  1. 1.大连理工大学航空航天学院，大连 116024；
    2.大连理工大学工业装备结构分析国家重点实验室，大连 116024
  • 收稿日期:2017-01-19 修回日期:2017-06-22 出版日期:2017-09-15 发布日期:2017-09-25
  • 基金资助:

    国家自然科学基金（11572069，11502040，11432010）；中央高校基本科研业务费专项资金（DUT16ZD225）

On Orbit Identification of the Moment of Inertia for a Spacecraft with Flexible Appendages during a Large Angle Maneuver

HE Xiao, TAN Shu jun, WU Zhi gang   

  1. 1. School of Aeronautics and Astronautics, Dalian University of Technology, Dalian 116024，China;
    2. State Key Laboratory of Structural Analysis for Industrial Equipment, Dalian 116024，China
  • Received:2017-01-19 Revised:2017-06-22 Online:2017-09-15 Published:2017-09-25

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摘要：

针对大角度机动情况下带挠性附件航天器转动惯量在轨辨识的问题，提出一种将转动惯量参数估计和挠性附件状态估计相结合的并发递推算法。该算法以大角度机动情况下带挠性附件航天器的非线性动力学模型为基础，分别利用广义卡尔曼滤波做挠性附件振动模态的状态估计，最小二乘法做转动惯量的参数估计。最后通过并发递推算法将二者结合，完成了带挠性附件航天器的转动惯量参数辨识。为了提高算法的效率，采用一步最小二乘、多步广义卡尔曼滤波并发递推的算法。仿真结果表明,该辨识方法兼具高精度、高效率，并且算法有一定的抗干扰能力。

关键词: 挠性附件, 转动惯量, 在轨参数辨识, 广义卡尔曼滤波, 最小二乘

Abstract:

For the problem of the on-orbit identification of the moment of inertia for a spacecraft with flexible appendages during a large-angle maneuver, a concurrent recursive algorithm is proposed in this paper, which combines the estimation of the inertia parameters with the state estimation of the flexible appendages’ vibration modes. The algorithm is based on the nonlinear dynamic model of a spacecraft with flexible appendages during a large-angle maneuver. The extended Kalman filter is used to estimate the states of the flexible appendages’ vibration modes, and the least square method is used to estimate the parameters of the moment of inertia. Finally, the inertia parameters of the spacecraft are obtained by the concurrent recursive algorithm. In order to improve the efficiency of the algorithm, a recursive algorithm based on one-step least square method and multi-step extended Kalman filter is proposed. Simulation results show that the proposed algorithm not only improves the computational accuracy and efficiency, but also has the capability of anti-interference.

Key words: Flexible appendages, Moment of inertia, On orbit parameter identification, Extended Kalman filter (EKF), Least square

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