Improving the Dynamic Accuracy of Elastic Industrial Robot Joint by Algebraic Identification Approach

Marouene Oueslati 1, 2 Richard Béarée 1 Olivier Gibaru 1, 2 George Moraru 1
2 NON-A - Non-Asymptotic estimation for online systems
Inria Lille - Nord Europe, CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189
Abstract : In this paper, an improvement of the dynamic accuracy of a flexible robot joint is addressed. Based on the observation of the measured axis deformation, a simplified elastic joint model is deduced. In the first step, the non-linear model component's is analyzed and identified in the cases of the gravity bias and the friction term. In the second step, a non asymptotically algebraic fast identification of the oscillatory behavior of the robot axis is introduced. Finally, the performances of the identification approach are exploited in order to improve the dynamic accuracy of a flexible robot axis. This is done experimentally by the combination of the adaptation of the jerk time profile to reduce the end-point vibration and the model-based precompensation of the end-point tracking error.
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Marouene Oueslati, Richard Béarée, Olivier Gibaru, George Moraru. Improving the Dynamic Accuracy of Elastic Industrial Robot Joint by Algebraic Identification Approach. 1st International Conference on Systems and Computer Science, Aug 2012, LILLE, France. ⟨hal-00714545⟩

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