Adaptive Fuzzy Modal Matching of Capacitive Micromachined Gyro Electrostatic Controlling

A fuzzy PI controller was utilized to realize the modal matching between a driving and detecting model. A simulation model was built to study electrostatic decoupling controlling technology. The simulation results show that the modal matching can be gained by the fuzzy PI controller. The frequency d...

Descripción completa

Detalles Bibliográficos
Autores principales: Cheng, Li, Liu, Ruimin, Guo, Shumin, Zheng, Gaofeng, Liu, Yifang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10490791/
https://www.ncbi.nlm.nih.gov/pubmed/37687879
http://dx.doi.org/10.3390/s23177422
_version_ 1785103922654871552
author Cheng, Li
Liu, Ruimin
Guo, Shumin
Zheng, Gaofeng
Liu, Yifang
author_facet Cheng, Li
Liu, Ruimin
Guo, Shumin
Zheng, Gaofeng
Liu, Yifang
author_sort Cheng, Li
collection PubMed
description A fuzzy PI controller was utilized to realize the modal matching between a driving and detecting model. A simulation model was built to study electrostatic decoupling controlling technology. The simulation results show that the modal matching can be gained by the fuzzy PI controller. The frequency difference between the driving mode and the detection mode is less than 1 Hz, and the offset of the input DC is smaller than 0.6 V. The optimal proportionality factor and integral coefficient are 1.5 and 20, respectively. The fuzzy PI controlling technology provides a good way for the parameter optimization to gain modal matching of micro gyro, via which the detecting accuracy and stability can be improved greatly.
format Online
Article
Text
id pubmed-10490791
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-104907912023-09-09 Adaptive Fuzzy Modal Matching of Capacitive Micromachined Gyro Electrostatic Controlling Cheng, Li Liu, Ruimin Guo, Shumin Zheng, Gaofeng Liu, Yifang Sensors (Basel) Article A fuzzy PI controller was utilized to realize the modal matching between a driving and detecting model. A simulation model was built to study electrostatic decoupling controlling technology. The simulation results show that the modal matching can be gained by the fuzzy PI controller. The frequency difference between the driving mode and the detection mode is less than 1 Hz, and the offset of the input DC is smaller than 0.6 V. The optimal proportionality factor and integral coefficient are 1.5 and 20, respectively. The fuzzy PI controlling technology provides a good way for the parameter optimization to gain modal matching of micro gyro, via which the detecting accuracy and stability can be improved greatly. MDPI 2023-08-25 /pmc/articles/PMC10490791/ /pubmed/37687879 http://dx.doi.org/10.3390/s23177422 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Cheng, Li
Liu, Ruimin
Guo, Shumin
Zheng, Gaofeng
Liu, Yifang
Adaptive Fuzzy Modal Matching of Capacitive Micromachined Gyro Electrostatic Controlling
title Adaptive Fuzzy Modal Matching of Capacitive Micromachined Gyro Electrostatic Controlling
title_full Adaptive Fuzzy Modal Matching of Capacitive Micromachined Gyro Electrostatic Controlling
title_fullStr Adaptive Fuzzy Modal Matching of Capacitive Micromachined Gyro Electrostatic Controlling
title_full_unstemmed Adaptive Fuzzy Modal Matching of Capacitive Micromachined Gyro Electrostatic Controlling
title_short Adaptive Fuzzy Modal Matching of Capacitive Micromachined Gyro Electrostatic Controlling
title_sort adaptive fuzzy modal matching of capacitive micromachined gyro electrostatic controlling
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10490791/
https://www.ncbi.nlm.nih.gov/pubmed/37687879
http://dx.doi.org/10.3390/s23177422
work_keys_str_mv AT chengli adaptivefuzzymodalmatchingofcapacitivemicromachinedgyroelectrostaticcontrolling
AT liuruimin adaptivefuzzymodalmatchingofcapacitivemicromachinedgyroelectrostaticcontrolling
AT guoshumin adaptivefuzzymodalmatchingofcapacitivemicromachinedgyroelectrostaticcontrolling
AT zhenggaofeng adaptivefuzzymodalmatchingofcapacitivemicromachinedgyroelectrostaticcontrolling
AT liuyifang adaptivefuzzymodalmatchingofcapacitivemicromachinedgyroelectrostaticcontrolling

Ejemplares similares