DocumentCode :
1055110
Title :
Parameter estimation for excavator arm using generalized Newton method
Author :
Zweiri, Y.H. ; Seneviratne, L.D. ; Althoefer, Kaspar
Author_Institution :
Dept. of Mech. Eng., King´´s Coll. London, UK
Volume :
20
Issue :
4
fYear :
2004
Firstpage :
762
Lastpage :
767
Abstract :
A robust, fast, and simple technique for the experimental identification of the link parameters (mass, inertia, and length) and friction coefficients of a full-scale excavator arm is presented. This new technique, based on the generalized Newton method (GNM), estimates unknown individual parameters of the excavator arm dynamic equations. The technique can be used when the number of equations is different from the number of estimated variables. Using experimental data from a full-scale field Combat Engineer Excavator (CEE), the values of link parameters and friction coefficients are successfully identified. The identified parameters are compared with known values, and shown to be in agreement. The method is compared with the least square method, and shows that the GNM is better in terms of prediction accuracy and robustness to noise. Further, the joint positions predicted by the analytical model using the identified parameters are validated against different experimental trajectories, showing very good agreement. The experimental data was obtained in collaboration with QinetiQ Ltd. (Hampshire, U.K.). The technique presented in this paper is general and can be applied to any manipulator.
Keywords :
Newton method; excavators; least mean squares methods; manipulator dynamics; parameter estimation; combat engineer excavator; excavator arm dynamic equation; experimental identification; friction coefficients; generalized Newton method; least square method; parameter estimation; Accuracy; Analytical models; Data engineering; Differential equations; Friction; Least squares methods; Newton method; Noise robustness; Parameter estimation; Trajectory; Excavator arm dynamics; GNM; full-scale field experiment; generalized Newton method; parameter estimation;
fLanguage :
English
Journal_Title :
Robotics, IEEE Transactions on
Publisher :
ieee
ISSN :
1552-3098
Type :
jour
DOI :
10.1109/TRO.2004.829476
Filename :
1321167
Link To Document :
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