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Tracking control of a flexible-link manipulator using neural networks: experimental results

Published online by Cambridge University Press:  24 June 2002

H.A. Talebi
Affiliation:
Dept. of Electrical Engineering, AmirKabir University, Tehran (Iran) 15914
K. Khorasani
Affiliation:
Dept. of Electrical and Computer Engineering, Concordia University, Montreal, Quebec (Canada) H3G 1M8
R. V. Patel
Affiliation:
Dept. of Electrical and Computer Engineering, University of Western Ontario, London, Ontario (Canada) N6A 5B9

Abstract

In this paper, the problem of tip position tracking control of a flexible-link manipulator is considered. Two neural network schemes are presented. In the first scheme, the controller is composed of a stabilizing joint PD controller and a neural network tracking controller. The objective is to simultaneously achieve hub-position tracking and control of the elastic deflections at the tip. In the second scheme, tracking control of a point along the arm is considered to avoid difficulties associated with the output feedback control of a non-minimum phase flexible manipulator. A separate neural network is employed for determining an appropriate output to be used for feedback. The controller is also composed of a neural network tracking controller and a stabilizing joint PD controller. Experimental results on a single-link flexible manipulator show that the proposed networks result in significant improvements in the system response with an increase in controller dynamic range despite changes in the desired trajectory.

Type
Research Article
Copyright
© 2002 Cambridge University Press

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