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A Terminal Sliding Mode with a Neural Network for an Exoskeleton Electric-Drive System

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Abstract

This paper describes a control algorithm for the sliding mode of a lower-extremity exoskeleton model with a neural network for elimination of external perturbances and uncertainties. The sliding control of rapid action is used for achievement of rapid convergence in finite time, absence of singularity, and suppression of oscillations. The neural network allows the efficiency of the regulator inside the boundary layer to be improved. The analysis of the asymptotic stability of the closed system is confirmed by the Lyapunov stability criterion guaranteeing the condition of sliding. The efficiency of the proposed control method has been proven using simulation in the MATLAB software, including the construction of a five-joint mathematical model of a lower-extremity exoskeleton.

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REFERENCES

  1. Truong, D.D., Belov, M.P., and Phuong, T.H., Development of mathematical model and subordinate control for nonlinear electric drivers of exoskeleton, IV Int. Conf. on Control in Technical Systems (CTS), St. Petersburg, 2021, IEEE, 2021, pp. 131–134. https://doi.org/10.1109/CTS53513.2021.9562831

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Author information

Authors and Affiliations

  1. St. Petersburg Electrotechnical University “LETI”, 197022, St. Petersburg, Russia

    L. P. Kozlova

  2. Le Quy Don Technical University, Hanoi, Vietnam

    D. D. Chyong

Authors
  1. L. P. Kozlova
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  2. D. D. Chyong
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Corresponding author

Correspondence to L. P. Kozlova.

Additional information

Translated by I. Moshkin

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Kozlova, L.P., Chyong, D.D. A Terminal Sliding Mode with a Neural Network for an Exoskeleton Electric-Drive System. Russ. Electr. Engin. 94, 186–190 (2023). https://doi.org/10.3103/S1068371223030082

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  • DOI: https://doi.org/10.3103/S1068371223030082

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