Hostname: page-component-cd9895bd7-q99xh Total loading time: 0 Render date: 2024-12-23T16:31:09.943Z Has data issue: false hasContentIssue false
  • English
  • Français

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).
Get access Rights & Permissions [Opens in a new window]

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

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)