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A separable prediction error method for robot identification

Brunot, Mathieu and Janot, Alexandre and Carrillo, Francisco Javier and Gautier, Maxime A separable prediction error method for robot identification. (2016) In: 7th IFAC Symposium on Mechatronic Systems, 5 September 2016 - 8 September 2016 (Loughborough University, United Kingdom).

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Official URL: http://dx.doi.org/10.1016/j.ifacol.2016.10.650

Abstract

The Prediction Error Method, developed in the field of system identification, handles the identification of discrete time noise model for systems linear with respect to the states and the parameters. However, robots are represented by continuous time models, which are not linear with respect to the states. In this article, we consider the issue of robot identification, taking into account the physical parameters as well as the noise model in order to improve the accuracy of the estimates. Thus, we developed a new technique to tackle this problem. The experimental results tend to show a real improvement in the estimation accuracy.

Item Type:Conference or Workshop Item (Paper)
Additional Information:Thanks to Elsevier editor. The definitive version is available at : http://www.sciencedirect.com/science/journal/24058963
HAL Id:hal-01490600
Audience (conference):International conference proceedings
Uncontrolled Keywords:
Institution:Université de Toulouse > Institut National Polytechnique de Toulouse - INPT (FRANCE)
French research institutions > Office National d'Etudes et Recherches Aérospatiales - ONERA (FRANCE)
Other partners > Université de Nantes (FRANCE)
Laboratory name:
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Deposited By: Mathieu Brunot
Deposited On:03 Feb 2017 14:36

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