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

Khalid A Alattas; Ardashir Mohammadzadeh; Saleh Mobayen; Ayman A Aly; Bassem F Felemban; Mai The Vu

doi:10.3390/mi12111390

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

Micromachines (Basel). 2021 Nov 12;12(11):1390. doi: 10.3390/mi12111390.

Authors

Khalid A Alattas¹, Ardashir Mohammadzadeh², Saleh Mobayen³, Ayman A Aly⁴, Bassem F Felemban⁴, Mai The Vu⁵

Affiliations

¹ Department of Computer Science and Artificial Intelligence, College of Computer Science and Engineering, University of Jeddah, Jeddah 23890, Saudi Arabia.
² Independent Researcher, Baku 1148, Azerbaijan.
³ Future Technology Research Center, National Yunlin University of Science and Technology, Douliu 64002, Taiwan.
⁴ Department of Mechanical Engineering, College of Engineering, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia.
⁵ School of Intelligent Mechatronics Engineering, Sejong University, Seoul 05006, Korea.

Abstract

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.

Keywords: LMI set; MEMS gyroscopes; data-driven control; fuzzy system; learning algorithm; machine learning.

Grants and funding

TURSP-2020/260/Taif University Researchers Supporting Project