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A Novel Sliding Mode Control for Human Upper Extremity with Gravity Compensation

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Cognitive Internet of Things: Frameworks, Tools and Applications (ISAIR 2018)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 810))

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Abstract

The paper studied the reaching movements of redundant human upper extremity muscles by a sliding mode control based on fuzzy adaptive scale adjustment. A two-link planar human musculoskeletal arm model is adopted on the basis of the Hill type with six redundant muscles. The study focused on the gravity compensation for the muscle input during the reaching movements process. Through the fuzzy adaptive system, the sliding mode controller may achieve adaptive approximation of switching scale so as to eliminate chattering. The numerical simulations are performed in order to verify the control. The results revealed that the human upper extremity can very well accomplish the reaching moments with proposed sliding mode controller.

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Acknowledgements

This work was supported by the Natural Science Foundation of the Jiangsu [grant numbers BK20171019].

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Authors and Affiliations

  1. College of Electrical Engineering and Control Science, Nanjing Tech University, Nanjing, China

    Ting Wang & Wen Qin

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  1. Ting Wang
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  2. Wen Qin
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Correspondence to Ting Wang .

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Editors and Affiliations

  1. Department of Mechanical and Control Engineering, Kyushu Institute of Technology, Kitakyushu, Japan

    Huimin Lu

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Wang, T., Qin, W. (2020). A Novel Sliding Mode Control for Human Upper Extremity with Gravity Compensation. In: Lu, H. (eds) Cognitive Internet of Things: Frameworks, Tools and Applications. ISAIR 2018. Studies in Computational Intelligence, vol 810. Springer, Cham. https://doi.org/10.1007/978-3-030-04946-1_7

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