Nuclear Engineering and Technology

Korean Nuclear Society (한국원자력학회)
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Position error compensation of the multi-purpose overload robot in nuclear power plants

  • Qin, Guodong (College of Mechanical & Electrical Engineering, Nanjing University of Aeronautics & Astronautics) ;
  • Ji, Aihong (College of Mechanical & Electrical Engineering, Nanjing University of Aeronautics & Astronautics) ;
  • Cheng, Yong (Institute of Plasma Physics, Chinese Academy of Science) ;
  • Zhao, Wenlong (Institute of Plasma Physics, Chinese Academy of Science) ;
  • Pan, Hongtao (Institute of Plasma Physics, Chinese Academy of Science) ;
  • Shi, Shanshuang (Institute of Plasma Physics, Chinese Academy of Science) ;
  • Song, Yuntao (Institute of Plasma Physics, Chinese Academy of Science)
  • Received : 2020.09.10
  • Accepted : 2021.02.07
  • Published : 2021.08.25
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Abstract

The Multi-Purpose Overload Robot (CMOR) is a key subsystem of China Fusion Engineering Test Reactor (CFETR) remote handling system. Due to the long cantilever and large loads of the CMOR, it has a large rigid-flexible coupling deformation that results in a poor position accuracy of the end-effector. In this study, based on the Levenberg-Marquardt algorithm, the spatial grid, and the linearized variable load principle, a variable parameter compensation model was designed to identify the parameters of the CMOR's kinematics models under different loads and at different poses so as to improve the trajectory tracking accuracy. Finally, through Adams-MATLAB/Simulink, the trajectory tracking accuracy of the CMOR's rigid-flexible coupling model was analyzed, and the end position error exceeded 0.1 m. After the variable parameter compensation model, the average position error of the end-effector became less than 0.02 m, which provides a reference for CMOR error compensation.

Keywords

Acknowledgement

This work was supported by the National Natural Science Foundation of China (Grant Nos. 11802305, 51875281, and 51861135306), the China National Special Project for Magnetic Confinement Fusion Science Program (Grant No. 2017YFE0300503), and the Fundamental Research Funds for the Central Universities (Grant No. NP2018112).

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