An automatic real-time mode-matching MEMS gyroscope with fuzzy and neural network control

Author

He, C.H. ; Zhao, Q.C. ; Liu, D.C. ; Dong, L.G. ; Yang, Z.C. ; Yan, G.Z.

Author_Institution

Nat. Key Lab. of Sci. & Technol. on Micro/Nano Fabrication, Peking Univ., Beijing, China

fYear

2013

fDate

16-20 June 2013

Firstpage

54

Lastpage

57

Abstract

This paper reports a novel method to accomplish automatic and real-time mode-matching control for a MEMS vibratory gyroscope based on fuzzy and neural network algorithms. Experimental results demonstrate that it only needs about 8 seconds to fulfil mode-matching automatically in the fuzzy control system, and a mismatching error lower than 0.32Hz is achieved over the temperature range from -40°C to 80°C in the neural network real-time control system. The scale factor of the mode-matched gyroscope with the closed loop controlled sense mode is measured to be 65.9 mV/deg/s with nonlinearity about 0.03%, and the bias instability and the angle random walk (ARW) are evaluated to be 0.68 deg/h and 0.028 deg/h^1/2, respectively.

Keywords

computerised instrumentation; fuzzy neural nets; gyroscopes; micromechanical devices; mode matching; real-time systems; angle random walk; automatic real-time mode-matching MEMS gyroscope; bias instability; closed loop controlled sense mode; fuzzy control; neural network control; scale factor; temperature -40 degC to 80 degC; Gyroscopes; Micromechanical devices; Neural networks; Real-time systems; Resonant frequency; Temperature control; Temperature measurement; MEMS gyroscope; fuzzy control; mode-matching; neural network control; real-time control;

fLanguage

English

Publisher

ieee

Conference_Titel

Solid-State Sensors, Actuators and Microsystems (TRANSDUCERS & EUROSENSORS XXVII), 2013 Transducers & Eurosensors XXVII: The 17th International Conference on

Conference_Location

Barcelona

Type

conf

DOI

10.1109/Transducers.2013.6626699

Filename

6626699