Parameter Estimation of MEMS Gyroscope Using Local State Estimation Methods

Abstract

The topic of unknown parameters estimation of a MEMS gyroscope system in real-time is proposed and discussed. The problem is tackled using state estimation methodology. It is formulated as joint state and parameter estimation where three local estimators are utilized. The estimates are used to control the proof mass trajectory adaptively where the system is enforced to operate at the resonant frequency of the system without damping coefficients. The estimate quality of the considered estimators is compared. Numerical simulation results indicate that the proposed approach provides a better estimate quality in comparison with the extended Kalman filter both in terms of convergence speed and quality of estimates.