Title: Identification of a deterministic Wiener system based on input least squares algorithm and direct residual method

Authors: Shaoxue Jing

Addresses: School of Physics and Electronic Electrical Engineering, Huaiyin Normal University, Huaian, Jiangsu 223300, China

Abstract: 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 systems 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 does not require calculating the intermediate variable. Second, an identification algorithm minimising the input prediction error is developed to obtain parameters of the Wiener system. Third, a numerical simulation and a case study verify the proposed algorithm. The proposed methods, with a little modification, can be applied to identify other block-oriented systems.

Keywords: order estimation; parameter estimation; Wiener system; residual analysis; input least squares algorithm; finite impulse response function.

DOI: 10.1504/IJMIC.2020.111620

International Journal of Modelling, Identification and Control, 2020 Vol.34 No.3, pp.208 - 216

Received: 12 Dec 2019
Accepted: 12 Feb 2020

Published online: 30 Nov 2020 *

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