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

Authors:
H. A. Talebi;K. Khorasani;R. V. Patel
Affiliations:
Dept. of Electrical Engineering, AmirKabir University, Tehran (Iran) 15914;Dept. of Electrical and Computer Engineering, Concordia University, Montreal, Quebec (Canada) H3G 1M8;Dept. of Electrical and Computer Engineering, University of Western Ontario, London, Ontario (Canada) N6A 5B9
Venue:
Robotica
Year:
2002

Citing 3
Cited 1

A singular perturbation approach to control of lightweight flexible manipulators

International Journal of Robotics Research
Neural network control for a closed-loop System using Feedback-error-learning

Neural Networks
Neural network based control schemes for flexible-link manipulators: simulations and experiments

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Parametric modelling approach using bacterial foraging algorithms for modelling of flexible manipulator systems

Engineering Applications of Artificial Intelligence

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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.