Model-Based Iterative Learning Control Applied to an Industrial Robot with Elasticity


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Hakvoort, W.B.J. and Aarts, R.G.K.M. and Dijk van, J. and Jonker, J.B. (2007) Model-Based Iterative Learning Control Applied to an Industrial Robot with Elasticity. In: 46th IEEE Conference on Decision and Control, 2007. IEEE, pp. 4185-4190. ISBN 9781424414970

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Abstract:In this paper model-based Iterative Learning Control (ILC) is applied to improve the tracking accuracy of an industrial robot with elasticity. The ILC algorithm iteratively updates the reference trajectory for the robot such that the predicted tracking error in the next iteration is minimised. The tracking error is predicted by a model of the closed-loop dynamics of the robot. The model includes the servo resonance frequency, the first resonance frequency caused by elasticity in the mechanism and the variation of both frequencies along the trajectory. Experimental results show that the tracking error of the robot can be reduced, even at frequencies beyond the first elastic resonance frequency.
Item Type:Book Section
Copyright:© 2008 IEEE
Faculty:
Engineering Technology (CTW)
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Link to this item:http://purl.utwente.nl/publications/61487
Official URL:http://dx.doi.org/10.1109/CDC.2007.4434366
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