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All Journal Bulletin of Electrical Engineering and Informatics
Atheel K. Abdul Zahra
University of Basrah
Electrical & Electronics Engineering

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A PSO optimized RBFNN and STSMC scheme for path tracking of robot manipulator Atheel K. Abdul Zahra; Turki Y. Abdalla
Bulletin of Electrical Engineering and Informatics Vol 12, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i5.5018

Abstract

This article presents the design of super twisting sliding mode control (STSMC) based on radial basis function neural network (RBFNN) for path tracking of two link robot manipulator. The proposed controller is utilized to guarantee and achieve that the surface of sliding can be in equilibrium point within a short time and avoid the problem of chattering at the output. The Lyapunov theory is used in presenting a new convergence proof. Also, the particle swarm optimization (PSO) algorithm is employed to give the optimal parameter values of the proposed controller. Simulation results explain the goodness of the proposed control method for trajectory tracking of 2-link robot manipulator when compared with SMC strategy. Results demonstrate that the the percentage improvement in mean square error (MSE) of using STSMC when compared with the standard SMC are 15.36%, 16.94% and 12.92%, for three different cases respectively.
Co-Authors Turki Y. Abdalla