Sensing and Control of MEMS Accelerometers Using Kalman Filter

Lili Dong; Kai Zhang

doi:10.1109/CCDC.2012.6244485

Sensing and Control of MEMS Accelerometers Using Kalman Filter

Lili Dong
, Kai Zhang

Research output: Contribution to journal › Article › peer-review

Abstract

A Kalman filter is designed and implemented for a MEMS capacitive accelerometer in order to filter out two major noise sources in the accelerometer, which are electronic noise and thermal mechanical noise (Brown noise). The dynamic modeling of the MEMS accelerometer is developed. A Kalman filter based force-to-rebalance controller is constructed on the model. Simulation results show that the Kalman filter based controller produces an excellent noise reduction, increases the dynamic range of the accelerometer, and stabilizes the accelerometer system under a closed-loop structure.

Original language	American English
Journal	Control and Decision Conference (CCDC), 2012 24th Chinese
DOIs	https://doi.org/10.1109/CCDC.2012.6244485
State	Published - Jan 1 2012

Disciplines

Electrical and Computer Engineering

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10.1109/CCDC.2012.6244485License: CC BY

Cite this

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title = "Sensing and Control of MEMS Accelerometers Using Kalman Filter",

abstract = " A Kalman filter is designed and implemented for a MEMS capacitive accelerometer in order to filter out two major noise sources in the accelerometer, which are electronic noise and thermal mechanical noise (Brown noise). The dynamic modeling of the MEMS accelerometer is developed. A Kalman filter based force-to-rebalance controller is constructed on the model. Simulation results show that the Kalman filter based controller produces an excellent noise reduction, increases the dynamic range of the accelerometer, and stabilizes the accelerometer system under a closed-loop structure.",

author = "Lili Dong and Kai Zhang",

year = "2012",

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doi = "10.1109/CCDC.2012.6244485",

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AU - Zhang, Kai

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N2 - A Kalman filter is designed and implemented for a MEMS capacitive accelerometer in order to filter out two major noise sources in the accelerometer, which are electronic noise and thermal mechanical noise (Brown noise). The dynamic modeling of the MEMS accelerometer is developed. A Kalman filter based force-to-rebalance controller is constructed on the model. Simulation results show that the Kalman filter based controller produces an excellent noise reduction, increases the dynamic range of the accelerometer, and stabilizes the accelerometer system under a closed-loop structure.

AB - A Kalman filter is designed and implemented for a MEMS capacitive accelerometer in order to filter out two major noise sources in the accelerometer, which are electronic noise and thermal mechanical noise (Brown noise). The dynamic modeling of the MEMS accelerometer is developed. A Kalman filter based force-to-rebalance controller is constructed on the model. Simulation results show that the Kalman filter based controller produces an excellent noise reduction, increases the dynamic range of the accelerometer, and stabilizes the accelerometer system under a closed-loop structure.

UR - https://engagedscholarship.csuohio.edu/enece_facpub/248

UR - http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=6244485abstractAccess=nouserType=inst

U2 - 10.1109/CCDC.2012.6244485

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JO - Control and Decision Conference (CCDC), 2012 24th Chinese

JF - Control and Decision Conference (CCDC), 2012 24th Chinese

ER -

Sensing and Control of MEMS Accelerometers Using Kalman Filter

Abstract

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