Temperature compensation for MEMS gyroscope based on hierarchical genetic algorithm and RBF neural network

Diansheng Chen; Zhihao Shao; Xusheng Lei; Tianmiao Wang

Temperature compensation for MEMS gyroscope based on hierarchical genetic algorithm and RBF neural network

Diansheng Chen^*
, Zhihao Shao
, Xusheng Lei
, Tianmiao Wang

^*Corresponding author for this work

Beihang University

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

1 Scopus citations

Abstract

The bias and scale factor of MEMS gyroscope are often influenced by temperature. To get the high precision attitude information, this paper proposed a temperature compensation scheme based on RBFNN. A new hierarchical genetic algorithm was also used to optimize the network construction and parameters. The effectiveness of the proposed scheme was shown by a series of tests. The error of the angular speed is controlled within ±0.5°/s under real conditions.

Original language	English
Pages (from-to)	2063-2066
Number of pages	4
Journal	Zhongguo Jixie Gongcheng/China Mechanical Engineering
Volume	20
Issue number	17
State	Published - 10 Sep 2009

Keywords

Error model
GA
MEMS gyro
Radial basis function neural network (RBFNN)
Temperature compensation

Cite this

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title = "Temperature compensation for MEMS gyroscope based on hierarchical genetic algorithm and RBF neural network",

abstract = "The bias and scale factor of MEMS gyroscope are often influenced by temperature. To get the high precision attitude information, this paper proposed a temperature compensation scheme based on RBFNN. A new hierarchical genetic algorithm was also used to optimize the network construction and parameters. The effectiveness of the proposed scheme was shown by a series of tests. The error of the angular speed is controlled within ±0.5°/s under real conditions.",

keywords = "Error model, GA, MEMS gyro, Radial basis function neural network (RBFNN), Temperature compensation",

author = "Diansheng Chen and Zhihao Shao and Xusheng Lei and Tianmiao Wang",

year = "2009",

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day = "10",

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journal = "Zhongguo Jixie Gongcheng/China Mechanical Engineering",

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T1 - Temperature compensation for MEMS gyroscope based on hierarchical genetic algorithm and RBF neural network

AU - Chen, Diansheng

AU - Shao, Zhihao

AU - Lei, Xusheng

AU - Wang, Tianmiao

PY - 2009/9/10

Y1 - 2009/9/10

N2 - The bias and scale factor of MEMS gyroscope are often influenced by temperature. To get the high precision attitude information, this paper proposed a temperature compensation scheme based on RBFNN. A new hierarchical genetic algorithm was also used to optimize the network construction and parameters. The effectiveness of the proposed scheme was shown by a series of tests. The error of the angular speed is controlled within ±0.5°/s under real conditions.

AB - The bias and scale factor of MEMS gyroscope are often influenced by temperature. To get the high precision attitude information, this paper proposed a temperature compensation scheme based on RBFNN. A new hierarchical genetic algorithm was also used to optimize the network construction and parameters. The effectiveness of the proposed scheme was shown by a series of tests. The error of the angular speed is controlled within ±0.5°/s under real conditions.

KW - Error model

KW - GA

KW - MEMS gyro

KW - Radial basis function neural network (RBFNN)

KW - Temperature compensation

UR - https://www.scopus.com/pages/publications/70349997223

M3 - 文章

AN - SCOPUS:70349997223

SN - 1004-132X

VL - 20

SP - 2063

EP - 2066

JO - Zhongguo Jixie Gongcheng/China Mechanical Engineering

JF - Zhongguo Jixie Gongcheng/China Mechanical Engineering

IS - 17

ER -

Temperature compensation for MEMS gyroscope based on hierarchical genetic algorithm and RBF neural network

Abstract

Keywords

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