System Identification with an Extended Threshold M-Estimator for Pseudo-Linear Models Structure

This paper deals with the problem of the estimation/validation of pseudo-linear models structure when outliers are present in the residuals. These corrupted data lead to unbounded modeling errors, involve long tail of the probability density function, and damage the model order estimation. Thus, from a ω-corrupted distribution model of these data, a parameterized robust estimation criterion (PREC) with an extended scaling factor in the Huber's norm and a robust final prediction error criterion (RFPE) based on M-estimates are proposed. Simulation results are given and the estimated orders of the robust models are derived from the new model validation criterion.