Study of ANFIS modeling algorithm for eliminating the fiber optic gyro nonlinear error

Yu Liu; Yanbin Sun; Yongle Lu; Dongfu Li; Leilei Li; Yingjun Pan

doi:10.3788/CJL200936s2.0027

Study of ANFIS modeling algorithm for eliminating the fiber optic gyro nonlinear error

Yu Liu^*, Yanbin Sun, Yongle Lu, Dongfu Li, Leilei Li, Yingjun Pan

^*Corresponding author for this work

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

1 Citation (Scopus)

Abstract

The drift of zero output is the main fact to impact measurement precision of the system. The temperature and nonlinearity which effect the measuremert precision the open-loop fiber optic gyro (O-FOG) are analyzed, and a novel model is presented to compensate errors caused by temperature and scale factor nonlinearity. The model is related with three factors: operate time, temperature and input angular rate. The precision can be improved by training. Experimental results show that it can eliminate effect of temperature drift and scale factor. The precision is improved in all temperature range, which shows the scheme's feasibility.

Original language	English
Pages (from-to)	27-29
Number of pages	3
Journal	Zhongguo Jiguang/Chinese Journal of Lasers
Volume	36
Issue number	SUPPL. 2
DOIs	https://doi.org/10.3788/CJL200936s2.0027
Publication status	Published - Dec 2009
Externally published	Yes

Keywords

Adaptable fuzzy neural inference system
Fiber optic gyro
Nonlinear
Optical devices
Scale factor
Zero drift

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10.3788/CJL200936s2.0027

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title = "Study of ANFIS modeling algorithm for eliminating the fiber optic gyro nonlinear error",

abstract = "The drift of zero output is the main fact to impact measurement precision of the system. The temperature and nonlinearity which effect the measuremert precision the open-loop fiber optic gyro (O-FOG) are analyzed, and a novel model is presented to compensate errors caused by temperature and scale factor nonlinearity. The model is related with three factors: operate time, temperature and input angular rate. The precision can be improved by training. Experimental results show that it can eliminate effect of temperature drift and scale factor. The precision is improved in all temperature range, which shows the scheme's feasibility.",

keywords = "Adaptable fuzzy neural inference system, Fiber optic gyro, Nonlinear, Optical devices, Scale factor, Zero drift",

author = "Yu Liu and Yanbin Sun and Yongle Lu and Dongfu Li and Leilei Li and Yingjun Pan",

year = "2009",

month = dec,

doi = "10.3788/CJL200936s2.0027",

language = "English",

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T1 - Study of ANFIS modeling algorithm for eliminating the fiber optic gyro nonlinear error

AU - Liu, Yu

AU - Sun, Yanbin

AU - Lu, Yongle

AU - Li, Dongfu

AU - Li, Leilei

AU - Pan, Yingjun

PY - 2009/12

Y1 - 2009/12

N2 - The drift of zero output is the main fact to impact measurement precision of the system. The temperature and nonlinearity which effect the measuremert precision the open-loop fiber optic gyro (O-FOG) are analyzed, and a novel model is presented to compensate errors caused by temperature and scale factor nonlinearity. The model is related with three factors: operate time, temperature and input angular rate. The precision can be improved by training. Experimental results show that it can eliminate effect of temperature drift and scale factor. The precision is improved in all temperature range, which shows the scheme's feasibility.

AB - The drift of zero output is the main fact to impact measurement precision of the system. The temperature and nonlinearity which effect the measuremert precision the open-loop fiber optic gyro (O-FOG) are analyzed, and a novel model is presented to compensate errors caused by temperature and scale factor nonlinearity. The model is related with three factors: operate time, temperature and input angular rate. The precision can be improved by training. Experimental results show that it can eliminate effect of temperature drift and scale factor. The precision is improved in all temperature range, which shows the scheme's feasibility.

KW - Adaptable fuzzy neural inference system

KW - Fiber optic gyro

KW - Nonlinear

KW - Optical devices

KW - Scale factor

KW - Zero drift

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SN - 0258-7025

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SP - 27

EP - 29

JO - Zhongguo Jiguang/Chinese Journal of Lasers

JF - Zhongguo Jiguang/Chinese Journal of Lasers

IS - SUPPL. 2

ER -

Study of ANFIS modeling algorithm for eliminating the fiber optic gyro nonlinear error

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Keywords

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