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SAM captures, stores, indexes, preserves, and distributes digital research material.Sat, 14 Jul 2018 04:21:31 GMT2018-07-14T04:21:31ZOn Algebraic Approach for MSD Parametric Estimation
http://hdl.handle.net/10985/10131
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.
Mon, 12 Sep 2011 00:00:00 GMThttp://hdl.handle.net/10985/101312011-09-12T00:00:00ZOUESLATI, 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.A simple and generic CAD/CAM approach for AFM probe-based machining
http://hdl.handle.net/10985/10565
BROUSSEAU, Emmanuel; ARNAL, Benoît; THIERY, Stéphane; NYIRI, Eric; GIBARU, Olivier
Atomic Force Microscopy (AFM) probe-based machining allows surface structuring at the nano-scale via the mechanical modification of material. This results from the direct contact between the tip of an AFM probe and the surface of a sample.
Given that AFM instruments are primarily developed for obtaining high-resolution topography information of inspected specimen, raster scanning typically defines the trajectory followed by the tip of an AFM probe. Although most AFM manufacturers provide software modules to perform user-defined tip displacement operations, such additional solutions can be limited with respect to 1) the range of tip motions that can be designed, 2) the level of automation when defining tip displacement strategies and 3) the portability for easily transferring trajectories data between different AFM instruments. In this context, this research presents a feasibility study, which aims to demonstrate the applicability of a simple and generic CAD/CAM approach when implementing AFM probe-based nano-machining for producing two-dimensional (2D) features with a commercial AFM instrument.
Sun, 01 Mar 2015 00:00:00 GMThttp://hdl.handle.net/10985/105652015-03-01T00:00:00ZBROUSSEAU, EmmanuelARNAL, BenoîtTHIERY, StéphaneNYIRI, EricGIBARU, OlivierAtomic Force Microscopy (AFM) probe-based machining allows surface structuring at the nano-scale via the mechanical modification of material. This results from the direct contact between the tip of an AFM probe and the surface of a sample.
Given that AFM instruments are primarily developed for obtaining high-resolution topography information of inspected specimen, raster scanning typically defines the trajectory followed by the tip of an AFM probe. Although most AFM manufacturers provide software modules to perform user-defined tip displacement operations, such additional solutions can be limited with respect to 1) the range of tip motions that can be designed, 2) the level of automation when defining tip displacement strategies and 3) the portability for easily transferring trajectories data between different AFM instruments. In this context, this research presents a feasibility study, which aims to demonstrate the applicability of a simple and generic CAD/CAM approach when implementing AFM probe-based nano-machining for producing two-dimensional (2D) features with a commercial AFM instrument.Improving the Dynamic Accuracy of Elastic Industrial Robot Joint by Algebraic Identification Approach
http://hdl.handle.net/10985/11401
OUESLATI, MAROUENE; BEARE, 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, MAROUENEBEARE, 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.FIR Filter-Based Online Jerk-Controlled Trajectory Generation
http://hdl.handle.net/10985/11402
BESSET, pierre; BEAREE, richard; GIBARU, olivier
This paper presents a novel approach to generate online jerk-limited trajectories for multi-DOF robotic systems. Finite Impulse Response filters are used to efficiently turn low
computational cost acceleration-limited profiles into jerk-limited profiles. Starting from a new setpoint, e.g. an event given by external sensors, and an arbitrary state of motion, i.e. with nonzero initial velocity and acceleration values, the proposed method can generate different shapes of jerk profile, including timeoptimal and fixed-time jerk-limited trajectories. A new definition of the velocity, acceleration and jerk kinematic limits can be
instantaneously taken into account during the motion. Moreover, the very low calculation time (less than 1 microsecond) makes it
possible to easily control a multi-DOF system during one control
cycle (classically about 1 millisecond), while preserving time
for other computer processing. The algorithm is experimentally
tested on the new 7-DOF industrial robot KUKA LWR iiwa.
Fri, 01 Jan 2016 00:00:00 GMThttp://hdl.handle.net/10985/114022016-01-01T00:00:00ZBESSET, pierreBEAREE, richardGIBARU, olivierThis paper presents a novel approach to generate online jerk-limited trajectories for multi-DOF robotic systems. Finite Impulse Response filters are used to efficiently turn low
computational cost acceleration-limited profiles into jerk-limited profiles. Starting from a new setpoint, e.g. an event given by external sensors, and an arbitrary state of motion, i.e. with nonzero initial velocity and acceleration values, the proposed method can generate different shapes of jerk profile, including timeoptimal and fixed-time jerk-limited trajectories. A new definition of the velocity, acceleration and jerk kinematic limits can be
instantaneously taken into account during the motion. Moreover, the very low calculation time (less than 1 microsecond) makes it
possible to easily control a multi-DOF system during one control
cycle (classically about 1 millisecond), while preserving time
for other computer processing. The algorithm is experimentally
tested on the new 7-DOF industrial robot KUKA LWR iiwa.