Fast Fractional-Order Terminal Sliding Mode Control With RBFNN Based Sliding Perturbation Observer for 7-DOF Robot Manipulator

Fast Fractional-Order Terminal Sliding Mode Control With RBFNN Based Sliding Perturbation Observer for 7-DOF Robot Manipulator

A new perturbation estimator, using radial basis function (RBF) neural networks (RBFNN) to modify the sliding perturbation observer (SPO), is proposed with the fast fractional-order terminal sliding mode control (FFOTSMC). It aims to control a seven-degree-of-freedom (7-DOF) robot manipulator. The n...

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Bibliographic Details
Main Authors: Wang Jie, Lee Min Cheol, Kim Jaehyung, Kim Hyun Hee
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Sliding mode control
fractional-order
robot manipulator
robust control
radial basis function
Online Access:https://ieeexplore.ieee.org/document/9416452/

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