Nonlinear Estimator Design for MEMS Gyroscope with Time-varying Angular Rate

Abstract

The problem of nonlinear parameter estimation of a MEMS gyroscope system is discussed. The MEMS gyroscope is considered with unknown parameters including mechanical structure imperfections and an unknown time-varying angular rate. The proposed approach uses the state estimation methodology to compensate the fabrication imperfections and to obtain a correct angular rate in real-time. The problem is formulated as a joint state and parameter estimation where the unscented Kalman filter is employed. For that purpose, a novel modeling technique approximating the angular rate using the first order Gauss-Markov process is proposed. To ensure persistent excitation of the system to achieve convergence of estimated parameters, both axes of the device are actively controlled by an appropriately designed adaptive controller. Properties of the proposed nonlinear estimation method are tested and validated through numerical simulations.