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Robust Sliding Mode Fuzzy Control of Industrial Robots using an Extended Kalman Filter Inverse Kinematic Solver

Khanesar, Mojtaba Ahmadieh; Branson, David

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DAVID BRANSON DAVID.BRANSON@NOTTINGHAM.AC.UK
Professor of Dynamics and Control



Abstract

This paper presents a sliding mode fuzzy control approach for industrial robots at their static and near static speed (linear velocities less than 5 cm/s). The extended Kalman filter with its covariance resetting is used to translate the coordinates from Cartesian to joint angle space. The translated joint angles are then used as a reference signal to control the industrial robot dynamics using a sliding mode fuzzy controller. The stability and robustness of the proposed controller is proven using an appropriate Lyapunov function in the presence of parameter uncertainty and unknown dynamic friction. The proposed controller is simulated on a 6-DOF industrial robot, namely the Universal Robot-UR5, considering the maximum allowable joint torques. It is observed that the proposed controller can successfully control UR5 under uncertainties in terms of unknown dynamic friction and parameter uncertainties. The tracking performance of the proposed controller is compared with that of the sliding mode control approach. The simulation results demonstrate superior performance of the proposed approach over the sliding mode control method in the presence of uncertainties.

Journal Article Type Article
Acceptance Date Feb 22, 2022
Online Publication Date Mar 3, 2022
Publication Date Mar 1, 2022
Deposit Date Mar 2, 2022
Publicly Available Date Mar 2, 2022
Journal Energies
Electronic ISSN 1996-1073
Peer Reviewed Peer Reviewed
Volume 15
Issue 5
Article Number 1876
DOI https://doi.org/10.3390/en15051876
Keywords Industrial robot control; Sliding mode fuzzy control; Inverse kinematic; extended Kal-23 man filter
Public URL https://nottingham-repository.worktribe.com/output/7532475
Publisher URL https://www.mdpi.com/1996-1073/15/5/1876

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