Robust Parameter Estimation for a Class of Nonlinear System with EM Algorithm

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Abstract

This paper is concerned with the robust parameter estimation for linear parameter varying (LPV) finite impulse response (FIR) model. The practical process data are typically polluted by outliers and conventional parameter estimation methods may fail to derive an unbiased estimate. In order to deal with outliers, the Laplace noise model is adopted and the robust system model for the described parameter estimation problem is established. The robust parameter estimation for LPV FIR model is formulated and solved in the EM algorithm scheme and the equations to estimate all the unknown parameters are derived. The efficacy of the proposed method is verified through a numerical simulation and a chemical unit.

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Zhang, T., Liu, X., & Liu, X. (2020). Robust Parameter Estimation for a Class of Nonlinear System with EM Algorithm. IEEE Access, 8, 30797–30804. https://doi.org/10.1109/ACCESS.2020.2973211

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