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Adaptive control of a robot using neural networks

Published online by Cambridge University Press:  09 March 2009

D. T. Pham and
S. J. Oh
D. T. Pham
Affiliation:
Intelligent Systems Laboratory, School of Electrical, Electronic and Systems Engineering, University of Wales College of Cardiff, P. O. Box 917, Newport Rd, Cardiff CF2 1XH (UK).
S. J. Oh
Affiliation:
Intelligent Systems Laboratory, School of Electrical, Electronic and Systems Engineering, University of Wales College of Cardiff, P. O. Box 917, Newport Rd, Cardiff CF2 1XH (UK).
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Summary

This paper describes an adaptive control system for an articulated robot with n joints carrying a variable load. The robot is a complex nonlinear time-varying MIMO plant with dynamic interaction between its inputs and outputs. However, the design of the control system is relatively straightforward and does not require any prior knowledge about the plant. This is because the control system is based on using neural networks which can capture the dynamic characteristics of the plant automatically. Three neural networks are employed in total, the first to learn the dynamics of the robot, the second to model its inverse dynamics and the third, a copy of the second neural network, to control the robot.

Keywords

MIMO systemNeural networkAdaptive controlRobots

Information

Type
Articles
Information
Robotica , Volume 12 , Issue 6 , November 1994, pp. 553 - 561
Copyright
Copyright © Cambridge University Press 1994

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