Control of a robot manipulator and pendubot system using artificial neural networks

Authors:
Joseph Constantin;Chaïban Nasr;Denis Hamad
Affiliations:
Department of EE, Faculty of Engineering I, Lebanese University EL ARZ Street, Tripoli-North (Lebanon).;Laboratoire d'Analyse des Systèmes du Littoral. Université du Littoral Côte d'Opale – 50 rue Ferdinand Buisson, Cedex 699 62228 Calais (France).;Laboratoire d'Analyse des Systèmes du Littoral. Université du Littoral Côte d'Opale – 50 rue Ferdinand Buisson, Cedex 699 62228 Calais (France).
Venue:
Robotica
Year:
2005

Citing 3
Cited 1

Neural Networks: A Comprehensive Foundation

Neural Networks: A Comprehensive Foundation
Adaptive Neural Network Control of Robotic Manipulators

Adaptive Neural Network Control of Robotic Manipulators
Nonlinear adaptive trajectory tracking using dynamic neural networks

IEEE Transactions on Neural Networks

Dynamics model abstraction scheme using radial basis functions

Journal of Control Science and Engineering - Special issue on Dynamic Neural Networks for Model-Free Control and Identification

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Abstract

The paper introduces artificial neural networks for the conventional control of robotic systems for better tracking performance. Different advanced dynamic control techniques are explained and a new second order recursive algorithm has been developed to tune the weights of the neural network. The problem of real-time control of a Pendubot system in difficult situations has been addressed. Examples, such as positioning and balancing structures, are presented and performances are compared to a conventional PD controller.