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Research of manipulator trajectory tracking based on adaptive robust iterative learning control

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Abstract

The manipulator control system is a dynamic system with the stronger nonlinear coupling feature and the higher position repetitive precision. In order to solve the problems of quickly load changes, many random disturbances, big measurement error and difficult dynamic modeling in the manipulator system, we designed a PD adaptive robust iterative learning controller, established the two degrees of freedom manipulator dynamics equation and used the Lyapunov function to analyze the stability and convergence of the system. MATLAB simulation of manipulator trajectory tracking shows that the control method can effectively inhibit various disturbances which cause by parameter variations, nonlinear mechanical and non-models dynamic characteristics. So the proposed method can make the system achieve good performance and verify the effectiveness of the algorithm, and the efficiency increases by 8%.

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Acknowledgements

This work was supported by the youth backbone teachers training program of Henan colleges and universities under Grant No. 2016ggjs-287, and the project of science and technology of Henan province under Grant No. 172102210124.

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Authors and Affiliations

  1. State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, 100044, China

    Xiaokan Wang & Dong Hairong

  2. Henan Mechanical and Electrical Vocational College, Xinzheng, 451191, China

    Xiaokan Wang & Wang Qiong

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  1. Xiaokan Wang
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  2. Dong Hairong
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Correspondence to Wang Qiong.

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Wang, X., Hairong, D. & Qiong, W. Research of manipulator trajectory tracking based on adaptive robust iterative learning control. Cluster Comput 22 (Suppl 2), 3079–3086 (2019). https://doi.org/10.1007/s10586-018-1919-3

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  • DOI: https://doi.org/10.1007/s10586-018-1919-3

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