Title: Control of robot manipulators in task-space under uncertainties using neural network
Author: H.P. Singh, N. Sukavanam
Department of Mathematics, Indian Institute of Technology, Roorkee, Roorkee – 247667, Uttarakhand, India.
Department of Mathematics, Indian Institute of Technology, Roorkee, Roorkee – 247667, Uttarakhand, India
Abstract: In this paper, neural network-based controller is designed for the tracking control of robot manipulators in task-space under uncertainties. Especially, this controller does not need prior information of the upper bound of the unstructured uncertainties. By adaptively estimating the upper bound using feedforward neural network, effects of unstructured uncertainties can be eliminated and asymptotic error convergence can be obtained for the closed-loop system. Simulation results are carried out for a two-link elbow robot manipulator to show the effectiveness of the control scheme.
Keywords: robot manipulators; feedforward neural networks; Lyapunov stability; task-space; unstructured uncertainties; intelligent control; robot control; error convergence; robot simulation.
Int. J. of Intelligent Engineering Informatics, 2011 Vol.1, No.2, pp.142 - 155
Available online: 19 May 2011