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Impedance control with on-line neural-network compensator for robot contact tasks

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Abstract

In this paper, a force-tracking impedance controller with an on-line neural-network compensator is shown to be able to track a reference force in the presence of unknown environmental dynamics. The controller can be partitioned into three parts. The computed torque method is used to linearize and decouple the dynamics of a manipulator. An impedance controller is then added to regulate the mechanical impedance between the manipulator and its environment. In order to track a reference force signal, an on-line neural network is used to compensate the effect of unknown parameters of the manipulator and environment.

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Authors and Affiliations

  1. Department of Mechanical Engineering, National Chung-Hsing University, Taichung, Taiwan

    Shih-Tin Lin & Jien-Shuin Lee

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  1. Shih-Tin Lin
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  2. Jien-Shuin Lee
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Lin, ST., Lee, JS. Impedance control with on-line neural-network compensator for robot contact tasks. J Intell Robot Syst 15, 389–399 (1996). https://doi.org/10.1007/BF00437603

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  • DOI: https://doi.org/10.1007/BF00437603

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