Joint Stiffness Identification from only Motor Force/Torque Data

Abstract : This paper deals with joint stiffness identification with only actual motor force/torque data instead of motor and load positions. The parameters are estimated by using the DIDIM method which needs only input data. This method was previously validated on a 6 DOF rigid robot and is now extended to flexible systems. The criterion to be minimized is the quadratic error between the measured actual motor force/torque and the simulated one. The optimal parameters are calculated with the Nelder - Mead simplex algorithm. An experimental setup exhibits the experimental identification results and shows the effectiveness of our approach.
Type de document :
Communication dans un congrès
IEEE Conference on Decision and Control and European Control Conference (CDC-ECC), Dec 2011, Orlando, United States. pp.5088-5093, 2011, 〈10.1109/CDC.2011.6160589〉
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https://hal.archives-ouvertes.fr/hal-00656818
Contributeur : Anthony Jubien <>
Soumis le : jeudi 5 janvier 2012 - 11:23:27
Dernière modification le : vendredi 13 octobre 2017 - 01:04:50

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Maxime Gautier, Alexandre Janot, Anthony Jubien, Pierre Olivier Vandanjon. Joint Stiffness Identification from only Motor Force/Torque Data. IEEE Conference on Decision and Control and European Control Conference (CDC-ECC), Dec 2011, Orlando, United States. pp.5088-5093, 2011, 〈10.1109/CDC.2011.6160589〉. 〈hal-00656818〉

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