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Effects of Nonlinearity on the Angular Drift Error of an Electrostatic MEMS Rate Integrating Gyroscope

Lookup NU author(s): Dr Zhongxu Hu, Dr Barry Gallacher

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This is the authors' accepted manuscript of an article that has been published in its final definitive form by IEEE, 2019.

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Abstract

Electrostatic MEMS Coriolis vibratory gyroscopes (CVG) are essentially nonlinear because of the capacitive transducers employed for the excitation and detection of resonance vibration. This paper investigates the influence of nonlinearity on the precession angle dependent bias error of a MEMS rate integrating gyroscope (RIG) and proposes a novel correction to minimize this effect. A linear model of CVGs is commonly used in the dynamic analysis and control of MEMS RIGs. The linear model predicts a 2nd harmonic angular drift error [1][2] due mainly to non-proportional damping. However, experimental results from previous work [3][4] demonstrate the existence of an additional 4th harmonic component in the precession rate, as well as in the resonant frequency and quadrature control. Analysis and removal of this high order error term will further improve the accuracy of RIG. Here, it is shown that high order angularly modulated drift error is the result of nonlinear damping, and that the stiffness nonlinearity is responsible for the 4th harmonics present in the fluctuation of the operating frequency and in the control for quadrature nulling. It is understood that nonlinear damping may be introduced electrically by the energy sustain state feedback control that uses nonlinear capacitive measurements. Nonlinearity correction is proposed to the capacitive displacement detection which significantly reduces the high order drift error. Simulation and experimental results are provided to validate the analysis. A DSP controlled MEMS RIG with nonlinearity correction exhibits an angular drift error of less than 0.2 deg/s.

Publication metadata

Author(s): Hu Z, Gallacher B

Publication type: Article

Publication status: Published

Journal: IEEE Sensors

Year: 2019

Volume: 19

Issue: 22

Pages: 10271-10280

Print publication date: 15/11/2019

Online publication date: 16/07/2019

Acceptance date: 15/07/2019

Date deposited: 16/07/2019

ISSN (print): 1424-8220

ISSN (electronic): 1424-8220

Publisher: IEEE

URL: https://doi.org/10.1109/JSEN.2019.2929352

DOI: 10.1109/JSEN.2019.2929352

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