SAM
https://sam.ensam.eu:443
The DSpace digital repository system captures, stores, indexes, preserves, and distributes digital research material.Fri, 18 Sep 2020 08:39:22 GMT2020-09-18T08:39:22ZImproving the Dynamic Accuracy of Elastic Industrial Robot Joint by Algebraic Identification Approach
http://hdl.handle.net/10985/11401
Improving the Dynamic Accuracy of Elastic Industrial Robot Joint by Algebraic Identification Approach
OUESLATI, Marouene; BEAREE, Richard; GIBARU, Olivier; MORARU, George
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.
Sun, 01 Jan 2012 00:00:00 GMThttp://hdl.handle.net/10985/114012012-01-01T00:00:00ZOUESLATI, MaroueneBEAREE, RichardGIBARU, OlivierMORARU, GeorgeIn 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.On Algebraic Approach for MSD Parametric Estimation
http://hdl.handle.net/10985/10131
On Algebraic Approach for MSD Parametric Estimation
OUESLATI, Marouene; THIERY, Stéphane; GIBARU, Olivier; BEAREE, Richard; MORARU, George
This article address the identification problem of the natural frequency and the damping ratio of a second order continuous system where the input is a sinusoidal signal. An algebra based approach for identifying parameters of a Mass Spring Damper (MSD) system is proposed and compared to the Kalman-Bucy filter. The proposed estimator uses the algebraic parametric method in the frequency domain yielding exact formula, when placed in the time domain to identify the unknown parameters. We focus on finding the optimal sinusoidal exciting trajectory which allow to minimize the variance of the identification algorithms. We show that the variance of the estimators issued from the algebraic identification method introduced by Fliess and Sira-Ramirez is less sensitive to the input frequency than the ones obtained by the classical recursive Kalman-Bucy filter. Unlike conventional estimation approach, where the knowledge of the statistical properties of the noise is required, algebraic method is deterministic and non-asymptotic. We show that we don't need to know the variance of the noise so as to perform these algebraic estimators. Moreover, as they are non-asymptotic, we give numerical results where we show that they can be used directly for online estimations without any special setting.
Sat, 01 Jan 2011 00:00:00 GMThttp://hdl.handle.net/10985/101312011-01-01T00:00:00ZOUESLATI, MaroueneTHIERY, StéphaneGIBARU, OlivierBEAREE, RichardMORARU, GeorgeThis article address the identification problem of the natural frequency and the damping ratio of a second order continuous system where the input is a sinusoidal signal. An algebra based approach for identifying parameters of a Mass Spring Damper (MSD) system is proposed and compared to the Kalman-Bucy filter. The proposed estimator uses the algebraic parametric method in the frequency domain yielding exact formula, when placed in the time domain to identify the unknown parameters. We focus on finding the optimal sinusoidal exciting trajectory which allow to minimize the variance of the identification algorithms. We show that the variance of the estimators issued from the algebraic identification method introduced by Fliess and Sira-Ramirez is less sensitive to the input frequency than the ones obtained by the classical recursive Kalman-Bucy filter. Unlike conventional estimation approach, where the knowledge of the statistical properties of the noise is required, algebraic method is deterministic and non-asymptotic. We show that we don't need to know the variance of the noise so as to perform these algebraic estimators. Moreover, as they are non-asymptotic, we give numerical results where we show that they can be used directly for online estimations without any special setting.