An Adaptive Parameter Identification Algorithm for Post-capture of a Tumbling Target

  • Jia Xu
  • Yang Yang
  • Yan Peng
  • Xiaomao Li
  • Shuanghua Zheng
  • Jianxiang CuiEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11743)


In this paper, a new parameter identification scheme is proposed for an unknown tumbling target captured by the space manipulator. Due to the unknown and various dynamic parameters of the target and the strong nonlinear characteristics of the manipulator, it is difficult to achieve the capture operation with high tracking accuracy and low energy consumption. Aiming at the challenge, the parameter identification model of free-floating space manipulator is established based on the momentum conservation principle. Then, the VDW-RLS (variable data-window-size recursive least square) algorithm is applied to identify the inertia parameters. VDW-RLS algorithm can adjust the size of data window online according to the change of system parameters. SimMechanics simulation platform is employed to implement the three-dimensional model of 7-DOFs manipulator system. Simulation results show that the proposed algorithm has a fast tracking performance and low misalignment in the inertial parameter identification of the multi-DOFs space manipulator, and the control effect can be further improved by using the identified dynamic parameters.


Space manipulator Parameter identification Momentum conservation VDW-RLS algorithm 



This study was supported by National Natural Science Foundation of China (Grant No. 61773254), Shanghai Sailing Program (Grant No. 17YF1406200), Shanghai Young Eastern Scholar Program (Grant No. QD2016029), and Shanghai civil-military integration program (Grant No. JMRH-2018-1043).


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Jia Xu
    • 1
  • Yang Yang
    • 1
  • Yan Peng
    • 1
  • Xiaomao Li
    • 1
  • Shuanghua Zheng
    • 1
  • Jianxiang Cui
    • 1
    Email author
  1. 1.Shanghai UniversityShanghaiChina

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