Investigation of a Symmetric Vibrating Gyroscope Characteristics Using a Simplified Dynamic Model

Ilia Rapoport, Daniel Choukroun

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this work a dynamical model for MEMS vibrational gyroscopes is developed that generalizes a previous work, allows for simpler but accurate qualitative and quantitative analysis of several sources of angular velocity measurement errors, and opens avenues for future developments in MEMS vibrational gyroscopes designs. The proposed model equations govern the dynamics of the amplitudes rather than the dynamics of the rapid oscillatory processes. The characteristics of this approximate model are significantly slower than the driving frequency. It allows a linear time-invariant analysis of the angular velocity measurement errors. These may be direct like a bias caused by the structural damping, or indirect, due e.g. to the unmatched frequencies between the drive and the sense channels. The approximate model was validated on a particular numerical example by examination and comparison of the frequency responses. A simple proportional feedback control was designed for both the drive and the quadrature loops, showing the potential impact of the feedback gains on the low-frequencies error. Being a linear time-invariant model, this model will easily lend itself to the development of more advanced control strategies.
Original languageEnglish
Title of host publicationAdvances in Estimation, Navigation, and Spacecraft Control
Subtitle of host publicationSelected Papers of the Itzhack Y. Bar-Itzhack Memorial Symposium on Estimation, Navigation, and Spacecraft Control
EditorsD. Choukroun , Y. Oshman , J. Thienel, M. Idan
PublisherSpringer Heidelberg
Pages329-348
Number of pages20
ISBN (Electronic)9783662447857
ISBN (Print)9783662447840
DOIs
StatePublished - Jan 2015

Fingerprint

Dive into the research topics of 'Investigation of a Symmetric Vibrating Gyroscope Characteristics Using a Simplified Dynamic Model'. Together they form a unique fingerprint.

Cite this