Identification of a Deterministic Wiener System Based on Input Prediction Error

The Wiener system is a type of block-oriented system that consists of a linear model followed in series with a static nonlinear element. In this work, two novel identification methods are proposed to estimate the order and parameters of a class of Wiener system whose linear part is a finite impulse response function and whose nonlinear inverse function is a polynomial. First, a direct order identification method using the input-output data rather than an unknown intermediate variable is designed to estimate the order of the linear part. The method decreases the computational cost and improves the accuracy of order estimation, because it doesn't require calculating the intermediate variable. Second, an identification algorithm minimizing the input prediction error is developed to obtain parameters of the Wiener system. Third, a numerical simulation verifies the proposed algorithm.