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

Published online by Cambridge University Press:  10 November 2005

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

Keywords

Pendubot systemArtificial neural networkTracking performance
Type
Research Article
Information
Robotica , Volume 23 , Issue 6 , November 2005 , pp. 781 - 784
Copyright
© 2005 Cambridge University Press

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