常海涛, 黄攀峰, 鹿振宇, 孟中杰, 张夷斋. 空间细胞机器人接管非合作目标时的交互式参数辨识方法[J]. 机器人, 2017, 39(2): 129-138. DOI: 10.13973/j.cnki.robot.2017.0129
引用本文: 常海涛, 黄攀峰, 鹿振宇, 孟中杰, 张夷斋. 空间细胞机器人接管非合作目标时的交互式参数辨识方法[J]. 机器人, 2017, 39(2): 129-138. DOI: 10.13973/j.cnki.robot.2017.0129
CHANG Haitao, HUANG Panfeng, LU Zhenyu, MENG Zhongjie, ZHANG Yizhai. Interactive Parameter Identification of Cellular Space Robots for Non-cooperative Spacecraft Takeover Control[J]. ROBOT, 2017, 39(2): 129-138. DOI: 10.13973/j.cnki.robot.2017.0129
Citation: CHANG Haitao, HUANG Panfeng, LU Zhenyu, MENG Zhongjie, ZHANG Yizhai. Interactive Parameter Identification of Cellular Space Robots for Non-cooperative Spacecraft Takeover Control[J]. ROBOT, 2017, 39(2): 129-138. DOI: 10.13973/j.cnki.robot.2017.0129

空间细胞机器人接管非合作目标时的交互式参数辨识方法

Interactive Parameter Identification of Cellular Space Robots for Non-cooperative Spacecraft Takeover Control

  • 摘要: 为应对日益复杂和多样的在轨服务需求,本文提出利用空间细胞机器人实施对非合作目标的接管控制.针对非合作目标接管控制中的惯性参数辨识问题,考虑到常用的递推最小二乘法依赖中心节点及计算量过大等不足,提出了一种适用于空间细胞机器人系统的交互式参数辨识算法,建立了质量、质心位置和惯性张量等惯性参数的辨识模型,利用细胞机器人之间的少量数据交互实现分布式和异步式的参数辨识.仿真结果表明,算法能够实现辨识结果的收敛性和一致性,辨识精度较高.最后分析了噪声、链路断开、拓扑结构和交互策略等因素对算法收敛性和一致性的影响,结果表明算法在噪声和链路断开等情况下仍能保证辨识结果的有效性.同时通过仿真分析验证了异步交互策略的优越性.

     

    Abstract: In order to execute diversified and complicated on-orbit service tasks, the cellular space robot (CSR) is proposed to perform takeover control for non-cooperative targets. To identify inertial parameters of the non-cooperative spacecraft in takeover control, an interactive parameter identification method for CSRs is proposed to reduce the central node dependency and huge computation requirement of the recursive least squares method which is commonly used. The parameter identification models for mass, center-of-mass and inertia tensor are presented respectively. The method presented is distributed and asynchronous, and requires only a few data interaction. Simulations are conducted to validate the convergence and consensus of the identification results, and high-accuracy identification is realized. More simulations show that the method proposed can achieve convergence and consensus under the influence of measurement noises, communication disconnection, communication topologies and interaction strategies, and obtain accurate results in the case of noises and disconnection. Meanwhile, the simulations validate the superiority of the asynchronous interaction over the synchronous interaction.

     

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