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

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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Veröffentlicht in:Micromachines (Basel) 2021-11, Vol.12 (11), p.1390
Hauptverfasser: Alattas, Khalid A., Mohammadzadeh, Ardashir, Mobayen, Saleh, Aly, Ayman A., Felemban, Bassem F., Vu, Mai The
Format: Artikel
Sprache:eng
Schlagworte:
Accuracy
Algorithms
Control stability
Controllers
data-driven control
Design
Distance learning
Fuzzy sets
fuzzy system
Fuzzy systems
Gyroscopes
learning algorithm
LMI set
machine learning
MEMS gyroscopes
Uncertainty
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Beschreibung
Zusammenfassung: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.
ISSN:2072-666X
2072-666X
DOI:10.3390/mi12111390