A New Data-Driven Control System for MEMSs Gyroscopes: Dynamics Estimation by Type-3 Fuzzy Systems

In this study, a novel data-driven control scheme is presented for MEMS gyroscopes (MEMS-Gs). The uncertainties are tackled by suggested type-3 fuzzy system with non-singleton fuzzification (NT3FS). Besides the dynamics uncertainties, the suggested NT3FS can also handle the input measurement errors....

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Autores principales: Khalid A. Alattas, Ardashir Mohammadzadeh, Saleh Mobayen, Ayman A. Aly, Bassem F. Felemban, Mai The Vu
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Publicado: MDPI AG 2021
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Acceso en línea:https://doaj.org/article/4773c643473d43c284b8bb423e35bb51
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spelling oai:doaj.org-article:4773c643473d43c284b8bb423e35bb512021-11-25T18:23:36ZA New Data-Driven Control System for MEMSs Gyroscopes: Dynamics Estimation by Type-3 Fuzzy Systems10.3390/mi121113902072-666Xhttps://doaj.org/article/4773c643473d43c284b8bb423e35bb512021-11-01T00:00:00Zhttps://www.mdpi.com/2072-666X/12/11/1390https://doaj.org/toc/2072-666XIn this study, a novel data-driven control scheme is presented for MEMS gyroscopes (MEMS-Gs). The uncertainties are tackled by suggested type-3 fuzzy system with non-singleton fuzzification (NT3FS). Besides the dynamics uncertainties, the suggested NT3FS can also handle the input measurement errors. The rules of NT3FS are online tuned to better compensate the disturbances. By the input-output data set a data-driven scheme is designed, and a new LMI set is presented to ensure the stability. By several simulations and comparisons the superiority of the introduced control scheme is demonstrated.Khalid A. AlattasArdashir MohammadzadehSaleh MobayenAyman A. AlyBassem F. FelembanMai The VuMDPI AGarticlefuzzy systemlearning algorithmMEMS gyroscopesmachine learningLMI setdata-driven controlMechanical engineering and machineryTJ1-1570ENMicromachines, Vol 12, Iss 1390, p 1390 (2021)
institution DOAJ
collection DOAJ
language EN
topic fuzzy system
learning algorithm
MEMS gyroscopes
machine learning
LMI set
data-driven control
Mechanical engineering and machinery
TJ1-1570
spellingShingle fuzzy system
learning algorithm
MEMS gyroscopes
machine learning
LMI set
data-driven control
Mechanical engineering and machinery
TJ1-1570
Khalid A. Alattas
Ardashir Mohammadzadeh
Saleh Mobayen
Ayman A. Aly
Bassem F. Felemban
Mai The Vu
A New Data-Driven Control System for MEMSs Gyroscopes: Dynamics Estimation by Type-3 Fuzzy Systems
description In this study, a novel data-driven control scheme is presented for MEMS gyroscopes (MEMS-Gs). The uncertainties are tackled by suggested type-3 fuzzy system with non-singleton fuzzification (NT3FS). Besides the dynamics uncertainties, the suggested NT3FS can also handle the input measurement errors. The rules of NT3FS are online tuned to better compensate the disturbances. By the input-output data set a data-driven scheme is designed, and a new LMI set is presented to ensure the stability. By several simulations and comparisons the superiority of the introduced control scheme is demonstrated.
format article
author Khalid A. Alattas
Ardashir Mohammadzadeh
Saleh Mobayen
Ayman A. Aly
Bassem F. Felemban
Mai The Vu
author_facet Khalid A. Alattas
Ardashir Mohammadzadeh
Saleh Mobayen
Ayman A. Aly
Bassem F. Felemban
Mai The Vu
author_sort Khalid A. Alattas
title A New Data-Driven Control System for MEMSs Gyroscopes: Dynamics Estimation by Type-3 Fuzzy Systems
title_short A New Data-Driven Control System for MEMSs Gyroscopes: Dynamics Estimation by Type-3 Fuzzy Systems
title_full A New Data-Driven Control System for MEMSs Gyroscopes: Dynamics Estimation by Type-3 Fuzzy Systems
title_fullStr A New Data-Driven Control System for MEMSs Gyroscopes: Dynamics Estimation by Type-3 Fuzzy Systems
title_full_unstemmed A New Data-Driven Control System for MEMSs Gyroscopes: Dynamics Estimation by Type-3 Fuzzy Systems
title_sort new data-driven control system for memss gyroscopes: dynamics estimation by type-3 fuzzy systems
publisher MDPI AG
publishDate 2021
url https://doaj.org/article/4773c643473d43c284b8bb423e35bb51
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