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Home > Thèses et HDR > Thèses en 2021

07/12/2021 - Jorge Ivan AYALA CUEVAS

by Laurent Krähenbühl - published on , updated on


  • Tuesday 7 December 2021 from 09:30 to 12:00 -

    Thèse Jorge Ivan AYALA CUEVAS

    Résumé :

    Performance Validation of MEMS Gyroscopes using Uncertain and Time-Varying Models

    Lieu : Ecole Centrale de Lyon, Bâtiment W1, Amphi 202

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Jorge Ivan Ayala Cuevas defends his PhD on Dec. 07, 2021 at 9:30 AM.
Place : Ecole Centrale de Lyon, bâtiment W1, Amphi 202.

Performance Validation of MEMS Gyroscopes using Uncertain and Time-Varying Models.

Jury :
Rapporteur : DEMOURANT Fabrice (ONERA)
Rapporteur : TURNER Matthew C. (University of Southampton)
Examinatrice : LESECQ Suzanne (CEA-Leti)
Examinateur : JUILLARD Jérôme (CentraleSupélec)
Invité : LE BLANC Christophe (ASYGN)
Directeur de thèse : SCORLETTI Gérard (Ecole Centrale de Lyon / Ampère)
Co-encadrant : KORNIIENKO Anton (Ecole Centrale de Lyon / Ampère)

Abstract :
MEMS gyroscopes are micro sensors that measure the angular rate of an object with respect to a reference frame by estimating the Coriolis force. The estimation is obtained thanks to the feedback control of the poorly damped spring-mass system oscillations coupled to synchronous demodulation. In spite of their attractive advantages, they suffer of manufacturing dispersion and an important sensitivity to temperature changes. The controllers are designed using strongly simplified models, without a certified performance level. This PhD work focuses on the pre-experimental performance validation of the designed control, using models that are more realistic, that is, approaching the validation as a dynamical system analysis problem. Due to synchronous demodulation, the system is modeled as a linear system with Harmonically Time-Varying (HTV) parameters, i.e. parameters that are sinusoidal functions of a given frequency. We address the analysis of Linear Harmonically Time-Varying (LHTV) systems by adopting an Integral Quadratic Constraints (IQC) approach. A key step to apply the IQC framework is to characterize the HTV parameters by IQCs defined by a set of functions named multipliers. In this work, we introduce new classes of HTV multipliers which dramatically reduce the conservatism of the analysis results.
Besides, commercialized MEMS gyroscope must verify accuracy and output noise specifications, defined by standards. We propose model-based performance criteria in order to evaluate these specifications. The most important accuracy specification is the Scale Factor Nonlinearity (SFNL), which is recast as robust optimization problem. The standard procedure to evaluate the output noise of MEMS gyroscopes is the Allan variance: a time-domain statistical tool computed from long-term measures of the gyroscope output. This experiment-based method is recast as a model-based analysis tool by adopting a generator filter approach. Different cases are investigated, from LTI models to classes of LHTV and uncertain models that are relevant for the MEMS gyroscope application. The proposed approaches are validated using experimental results. Finally, the proposed systems analysis tools are applied to the validation of alternative control strategies that require more complex architectures than the classical LTI control.

Keywords :
MEMS gyroscopes, model-based validation, system analysis, robustness, harmonically time-varying systems, IQC, scale factor non-linearity, Allan variance.

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