Results 101 to 110 of about 11,944 (194)

Drive-Mode Control for Vibrational MEMS Gyroscopes

IEEE Transactions on Industrial Electronics, 2009
This paper presents a novel design methodology and hardware implementation for the drive-mode control of vibrational micro-electro-mechanical systems gyroscopes. Assuming that the sense mode (axis) of the gyroscope is operating under open loop, the drive-mode controller compensates an undesirable mechanical spring-coupling term between the two ...
Lili Dong, David Avanesian
openaire   +2 more sources

Adaptive Control for MEMS Gyroscopes [PDF]

, 2002
This report presents a new adaptive operation strategy for MEMS z-axis gyroscopes. Specifically, a unified methodology is proposed for designing and analyzing the performance of a control algorithm that can identify and, in an adaptive fashion, compensate for most fabrication defects and perturbations affecting the behavior of a MEMS z-axis gyroscope ...
Park, Sungsu, Horowitz, Roberto, Tan, Chin-woo   +2 more
openaire   +1 more source

Interactive Errors Analysis and Scale Factor Nonlinearity Reduction Methods for Lissajous Frequency Modulated MEMS Gyroscope. [PDF]

Sensors (Basel), 2023
Li R, Wang X, Yan K, Chen Z, Ma Z, Wang X, Zhang A, Lu Q.   +7 more
europepmc   +1 more source

An automatic Q-factor matching method for eliminating 77% of the ZRO of a MEMS vibratory gyroscope in rate mode

Microsystems & Nanoengineering
Mismatching quality factors (Q-factors) is one of the main factors causing zero-rate output (ZRO) in degenerate (DE) Micro-Electro-Mechanical Systems (MEMS) vibratory gyroscopes.
Jingbo Ren, Tong Zhou, Yi Zhou, Yixuan Li, Yan Su   +4 more
doaj   +1 more source

Multi-scale prediction of MEMS gyroscope random drift based on EMD-SVR

Journal of Measurement Science and Instrumentation, 2020
To improve the prediction accuracy of micro-electromechanical systems（MEMS） gyroscope random drift series, a multi-scale prediction model based on empirical mode decomposition（EMD） and support vector regression（SVR） is proposed.
HE Jia-ning, ZHONG Ying, LI Xing-fei
doaj  

A 0.82 μVrms ultralow 1/f noise bandgap reference for a MEMS gyroscope. [PDF]

Microsyst Nanoeng, 2023
Zou J, Wei Q, Ju C, Liao H, Gu H, Xing B, Zhou B, Zhang R.   +7 more
europepmc   +1 more source

Development and Research of the Sensitive Element of the MEMS Gyroscope Manufactured Using SOI Technology. [PDF]

Micromachines (Basel), 2023
Naumenko D, Tkachenko A, Lysenko I, Kovalev A.   +3 more
europepmc   +1 more source

Adaptive Dynamic Analysis of MEMS Gyroscope Random Noise Based on PID-DAVAR. [PDF]

Micromachines (Basel), 2023
Zhang J, Li P, Yu Z, Liu J, Zhang X, Zhuang X.   +5 more
europepmc   +1 more source

Inclination Effect on the Periodic Response of a Symmetrical MEMS Gyroscope. [PDF]

Micromachines (Basel), 2022
Zhang L, Zhang H, Li X, Ji Y.
europepmc   +1 more source

Robust Control for MEMS Gyroscopes

, 2021
Les gyromètres MEMS sont composés de deux modes de vibration : drive et sense. Le fonctionnement est basé sur le transfert d’énergie entre ces modes dû à la force de Coriolis, qui est proportionnelle à la vitesse angulaire. En asservissant les oscillations du mode drive à une fréquence d’excitation donnée et en estimant la force de Coriolis, la vitesse
openaire   +1 more source