Temperature Error Compensation Method Based on Adaptive Neuro Fuzzy Inference for Fiber-optic Gyro

doi:10.3969/j.issn.1000-1093.2016.04.010

Abstract

Abstract: According to Shupe thermally induced non-reciprocity noise theory, the mechanism of the temperature drift of fiber-optic gyro is researched, and a temperature experiment with range of -15～50 ℃ is designed. A temperature error compensation model based on adaptive neuro fuzzy inference for fiber-optic gyro is established by using the adaptive neuro fuzzy inference system and the piecewise modeling method and constructing the training sample from the measured data. The proposed model is used to solve the problem of poor model matching, and can help to shorten the time of the gyro entering into the steady state. The calculated results show that the standard deviation of the temperature drift is reduced by 75.55% after compensation with the proposed method.

Key words: control science and technology, fiber-optic gyro, temperature drift, adaptive neuro fuzzy inference, error compensation, piecewise modeling

CLC Number:

TG156

FENG Ka-li， LI An， QIN Fang-jun， LI Feng. Temperature Error Compensation Method Based on Adaptive Neuro Fuzzy Inference for Fiber-optic Gyro[J]. Acta Armamentarii, 2016, 37(4): 641-647.

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