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Open AccessArticle

An Adaptive Neural Non-Singular Fast-Terminal Sliding-Mode Control for Industrial Robotic Manipulators

School of Electrical Engineering, University of Ulsan, 93 Daehak-ro, Nam-gu, Ulsan 680-749, Korea
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Appl. Sci. 2018, 8(12), 2562; https://doi.org/10.3390/app8122562
Received: 20 November 2018 / Revised: 6 December 2018 / Accepted: 7 December 2018 / Published: 10 December 2018
(This article belongs to the Special Issue Advanced Mobile Robotics)
In this study, a robust control strategy is suggested for industrial robotic manipulators. First, to minimize the effects of disturbances and dynamic uncertainties, while achieving faster response times and removing the singularity problem, a nonsingular fast terminal sliding function is proposed. Second, to achieve the proposed tracking trajectory and chattering phenomenon elimination, a robust control strategy is designed for the robotic manipulator based on the proposed sliding function and a continuous adaptive control law. Furthermore, the dynamical model of the robotic system is estimated by applying a radial basis function neural network. Thanks to those techniques, the proposed system can operate free of an exact robotic model. The suggested system provides high tracking accuracy, robustness, and fast response with minimal positional errors compared to other control strategies. Proof of the robustness and stability of the suggested system has been verified by the Lyapunov theory. In simulation analyses, the simulated results present the effectiveness of the suggested strategy for the joint position tracking control of a 3-degree of freedom (3-DOF) PUMA560 robot. View Full-Text
Keywords: non-singular fast-terminal sliding-mode control; industrial robotic manipulator; external disturbance; dynamic uncertainty; adaptive control law non-singular fast-terminal sliding-mode control; industrial robotic manipulator; external disturbance; dynamic uncertainty; adaptive control law
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Vo, A.T.; Kang, H.-J. An Adaptive Neural Non-Singular Fast-Terminal Sliding-Mode Control for Industrial Robotic Manipulators. Appl. Sci. 2018, 8, 2562.

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