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A direct approach to modeling an industrial robot from samples of input-output data

Published online by Cambridge University Press:  09 March 2009

Ajit M. Karnik  and
Naresh K. Sinha
Ajit M. Karnik
Affiliation:
Department of Electrical and Computer Engineering, McMaster University, Hamilton, Ontario (Canada)
Naresh K. Sinha
Affiliation:
Department of Electrical and Computer Engineering, McMaster University, Hamilton, Ontario (Canada)
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Summary

The increased demand on the performance and efficiency of industrial robots, has led to the design of sophisticated control systems. Such control systems require an accurate dynamic model of the system. A commonly used method of modeling an industrial robot, involves the description of a set of dynamic equations, relating actuator torques to loads and accelerations. These equations are generally quite complex and inconvenient for implementation on digital computers.

Another method often used for identification, is the ‘indirect method’, in which the transfer function is obtained in two steps. The discrete time model is first derived from samples of the input and output measurements, which is then transformed to the continuous-time model. A limitation of this method is that it requires the excitation to be of the ‘persistently exciting’ type, thus precluding the application of simple inputs like the step signal.

This paper describes a ‘direct’ method for identification of an ‘industrial robot’ from samples of input and output observations. Results of modeling an industrial robot and two simulations are presented. One of the simulations, and the industrial robot uses the step input as excitation. The other example was excited with an exponential input.

Type
Article
Information
Robotica , Volume 2 , Issue 3 , July 1984 , pp. 161 - 167
Copyright
Copyright © Cambridge University Press 1984

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