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Two trajectory tracking control methods for space hyper-redundant cable-driven robots considering model uncertainty

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Abstract

Space hyper-redundant cable-driven robots (SHCDRs) have a slender body structure and high dexterity, which is very suitable for complex and limited unstructured space environments. Due to the multi-level coupling relationship between motors, cables, joints, and tips, the accurate mathematical model is also uncertain, making the motion accuracy of the end-effector much lower than that of traditional industrial robots. Based on this, this article proposes two trajectory tracking control (TTC) methods for SHCDRs considering model uncertainty, one is based on model modification, and the other on two-layer iterative learning control (TLILC). This study first establishes a multi-level motion coupling model, and improve the inverse dynamics equation for the control requirements. Then, two different vision feedback-based TTC frameworks are developed. Further, both frameworks are solved by different iterative methods. Finally, in order to demonstrate the superiority of the proposed TTC methods, numerical simulation systems (including VC++, OSG, and MATLAB/Simulink) are conducted on a 12-DOF SHCDR to validate the two proposed methods. The results show that the proposed two vision-based TTC methods have higher tracking accuracy.

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Acknowledgements

This work was supported in part by the National Natural Science Foundation of China under Grant 62103454, the Guangdong Basic and Applied Basic Research Foundation under Grant 2019A1515110680, the Shenzhen Municipal Basic Research Project for Natural Science Foundation under Grant JCYJ20190806143408992, and the Fundamental Research Funds for the Central Universities, Sun Yat-sen University (Grant No. 2021qntd08). Thanks to the Prof. Darwin Lau from The Chinese University of Hong Kong for his precious comments that have significantly improved the completeness and quality of the ILC controller.

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Authors and Affiliations

  1. School of Intelligent Systems Engineering, Sun Yat-sen University, Shenzhen, 518107, China

    Jianqing Peng, Chi Zhang & Yu Han

  2. Guangdong Provincial Key Laboratory of Fire Science and Technology, Guangzhou, 510006, China

    Jianqing Peng & Yu Han

  3. School of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen, 518055, China

    Jianqing Peng

  4. Beijing Institute of Spacecraft System Engineering, Beijing, 100089, China

    Dongming Ge

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Correspondence to Jianqing Peng.

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PENG, ZHANG, GE, and HAN declare that they have no proprietary, financial, professional or other personal interest of any nature or kind in any product, service and/or company that could be construed as influencing the position presented in, or the review of, the manuscript entitled “Vision Feedback-based Trajectory Tracking Control Method of Space Hyper-Redundant Cable-Driven Robots”.

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Peng, J., Zhang, C., Ge, D. et al. Two trajectory tracking control methods for space hyper-redundant cable-driven robots considering model uncertainty. Multibody Syst Dyn 56, 123–152 (2022). https://doi.org/10.1007/s11044-022-09840-1

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