基于姿态信号分布测量的空间太阳能电站惯性张量参数辨识

doi:10.3901/JME.2024.16.209

机械工程学报 ›› 2024, Vol. 60 ›› Issue (16): 209-221.doi: 10.3901/JME.2024.16.209

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基于姿态信号分布测量的空间太阳能电站惯性张量参数辨识

倪智宇¹, 李自森¹, 邬树楠², 吴晨晨³

1. 沈阳航空航天大学航空宇航学院沈阳 110136;
2. 中山大学航空航天学院深圳 518107;
3. 南京理工大学物理学院南京 210094

收稿日期:2023-11-09 修回日期:2024-03-21 出版日期:2024-08-20 发布日期:2024-10-21
作者简介:倪智宇,男,1985年出生,博士,讲师,硕士研究生导师。主要研究方向为系统辨识研究。E-mail:nizhiyu@sau.edu.cn
邬树楠(通信作者),男,1982年出生,博士,副教授,博士研究生导师。主要研究方向为航天器动力学与控制、空间机器人动力学与控制等。E-mail:wushunan@mail.sysu.edu.cn
基金资助:
国家自然科学基金(11972102，51905527)、辽宁省自然科学基金(2021-MS-267)和辽宁省教育厅基本科研(JYTMS20230254)资助项目。

Inertia Tensor Parameter Identification of Space Solar Power Station Based on Distributed Measurement of Attitude Signal

NI Zhiyu¹, LI Zisen¹, WU Shunan², WU Chenchen³

1. College of Aerospace Engineering, Shenyang Aerospace University, Shenyang 110136;
2. School of Aeronautics and Astronautics, Sun Yat-sen University, Shenzhen 518107;
3. School of Physics, Nanjing University of Science and Technology, Nanjing 210094

Received:2023-11-09 Revised:2024-03-21 Online:2024-08-20 Published:2024-10-21

摘要/Abstract

摘要： 当空间结构的尺寸较大时，集中布置的姿态传感器测量得到的信号会受到柔性振动的明显影响。为了减小结构振动对于姿态信号测量的影响，研究空间太阳能电站的姿态传感器分布式布置问题，并提出一种变遗忘因子耦合最小二乘方法辨识该结构的惯性张量参数。该方法通过计算系统均方差来确定递推过程中的时变遗忘因子，之后基于姿态信号的分布式测量结果辨识得到系统的惯性张量参数。数值仿真结果表明对于这样一个大型柔性空间结构，姿态传感器的分布式布置能够在一定程度上降低振动对于姿态信号测量精度的影响，提高惯性张量参数的辨识精度。分析结果还证明了提出的算法能够有效地识别该大型柔性空间结构的惯性张量参数，具有抗噪声能力高和计算复杂度较低的特点。当量测信噪比为15 dB时，与传统的递推最小二乘方法相比，所提出的算法的平均相对误差的绝对值和相对值分别最大降低了25.4%和68.9%。

关键词: 惯性参数辨识, 空间太阳能电站, 传感器优化配置, 大型柔性结构, 变遗忘因子

Abstract: The signals by the attitude sensors with concentrated placement will be significantly affected by the flexible vibration when the size of space structure is large. To reduce the influence of structural vibration on the measured attitude signal, the distributed placement of attitude sensors in a space solar power station is studied, and a novel recursive method called variable forgetting factor coupled least squares is proposed to identify the inertia tensor parameters of the structure. The proposed method determines the time-varying forgetting factor in the recursive procedure by computing the system mean square deviation, and thus the inertia tensor parameters of the system are identified based on the distributed measurement results of attitude signals. The numerical simulation results indicate that for such a large flexible space structure, the distributed placement of attitude sensor can reduce the influence of vibration on the measurement accuracy of attitude signal to a certain extent, thereby increasing the identification accuracy of inertia tensor parameters. In addition, the analysis results also demonstrate that the proposed method can be used to effectively identify the inertia tensor parameters of the large flexible space structure and has high noise-immunity ability and low computational complexity. The absolute and relative values of the average relative error is decreased by approximately 25.4% and 68.9% maximum respectively on using the proposed recursive algorithm compared to that obtained using the conventional recursive least squares method when the measurement signal-to-noise-ratio is 15 dB.

Key words: inertial parameter identification, space solar power station, optimal sensor placement, large flexible structure, variable forgetting factor

中图分类号:

N945

倪智宇, 李自森, 邬树楠, 吴晨晨. 基于姿态信号分布测量的空间太阳能电站惯性张量参数辨识[J]. 机械工程学报, 2024, 60(16): 209-221.

NI Zhiyu, LI Zisen, WU Shunan, WU Chenchen. Inertia Tensor Parameter Identification of Space Solar Power Station Based on Distributed Measurement of Attitude Signal[J]. Journal of Mechanical Engineering, 2024, 60(16): 209-221.

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基于姿态信号分布测量的空间太阳能电站惯性张量参数辨识

Inertia Tensor Parameter Identification of Space Solar Power Station Based on Distributed Measurement of Attitude Signal

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