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Experimental Evaluation of Identification Schemes on a Direct Drive Robot

Published online by Cambridge University Press:  01 September 1997

Fernando Reyes
Affiliation:
División de Física Aplicada, CICESE, Apdo. Postal 2615, Adm. 1, Carretera Tijuana-Ensenada Km. 107, Ensenada, B.C. 22800, Mexico. E-mail: freyez@cicese.mx
Rafael Kelly
Affiliation:
División de Física Aplicada, CICESE, Apdo. Postal 2615, Adm. 1, Carretera Tijuana-Ensenada Km. 107, Ensenada, B.C. 22800, Mexico. E-mail: rkelly@cicese.mx

Abstract

This paper describes the experimental evaluation of three identification schemes to determine the dynamic parameters of a two degrees of freedom direct-drive robot. These schemes involve a recursive estimator while the regression models are formulated in continuous time. The fact that the total energy of robot manipulators can be represented as a linear relation in the inertial parameters, has motivated the suggestion in the literature of several regression models which are linear in a common dynamic parameter vector. Among them, in this paper we consider the schemes based on the filtered dynamic regression model, the supplied energy regression model and a new one proposed in this paper: the filtered power regression model. The underling recursive parameter estimator used in the experimental evaluation is the standard least-squares.

Type
Research Article
Copyright
© 1997 Cambridge University Press

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Footnotes

Work partially supported by CONACYT, Mexico.