Zero-Rate Offset Compensation for Dual-Mass Tuning Fork Micro-Machined Gyroscope Based on Back Propagation Neural Network

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

For the zero-rate offset of dual-mass tuning fork micro-machined gyroscope (DTMG), back propagation neural network (BPNN) is proposed to compensate the offset. The zero-rate offset data were tested as the training data and the verification data of BPNN. The experimental results prove that this method has strong nonlinear mapping capabilities. And it can effectively reduce the zero-rate offset of DTMG by more than one order of magnitude. Thus, DTMG can be applied to the field of inertial navigation with higher precision.

Original languageEnglish
Title of host publicationProceedings 2018 Chinese Automation Congress, CAC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages821-824
Number of pages4
ISBN (Electronic)9781728113128
DOIs
Publication statusPublished - 2 Jul 2018
Event2018 Chinese Automation Congress, CAC 2018 - Xi'an, China
Duration: 30 Nov 20182 Dec 2018

Publication series

NameProceedings 2018 Chinese Automation Congress, CAC 2018

Conference

Conference2018 Chinese Automation Congress, CAC 2018
Country/TerritoryChina
CityXi'an
Period30/11/182/12/18

Keywords

  • BPNN
  • DTMG
  • compensation
  • zero-rate offset

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