This paper deals with identifying the fractional-order noise parameters for MEMS gyroscopes under various temperature conditions. The significant contribution of the paper is to investigate the relation between the fractional noise model of MEMS devices and different ambient temperatures. In our paper, variance, correlation, and introduced estimation analysis methods have been meticulously applied to determine noise parameters with fractional-order dynamics.
View Article and Find Full Text PDFThis paper is devoted to identifying parameters of fractional order noises with application to noises obtained from MEMS accelerometer. The analysis and parameters estimation will be based on the Triple Estimation algorithm, which can simultaneously estimate state, fractional order, and parameter estimates. The capability of the Triple Estimation algorithm to fractional noises estimation will be confirmed by the sets of numerical analyses for fractional constant and variable order systems with Gaussian noise input signal.
View Article and Find Full Text PDFIn this paper, a method for states, parameters, and fractional order estimation is presented. The proposed method is an extension of the traditional dual estimation method and uses three blocks of filters with appropriate data interconnections. As the main part of the estimation algorithm, the Fractional Unscented Kalman Filter was used.
View Article and Find Full Text PDFPhilos Trans A Math Phys Eng Sci
May 2013
This paper presents the results of modelling the heat transfer process in heterogeneous media with the assumption that part of the heat flux is dispersed in the air around the beam. The heat transfer process in a solid material (beam) can be described by an integer order partial differential equation. However, in heterogeneous media, it can be described by a sub- or hyperdiffusion equation which results in a fractional order partial differential equation.
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