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Conflict of Interest: In relation to this article, we declare that there is no conflict of interest.

Publication history: Received September 21, 2007
Accepted December 13, 2007

This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/bync/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Improved system identification method for Hammerstein-Wiener processes

Su Whan Sung^† Cheol Ho Je Jietae Lee Dong Hyun Lee¹

Department of Chemical Engineering, Kyungpook National University, 1370 Sankyeok-dong, Buk-gu, Daegu 702-701, Korea ¹Department of Chemical Engineering, Sungkyunkwan University, 300 Chunchun, Jangan, Suwon 440-746, Korea

suwhansung@knu.ac.kr

Korean Journal of Chemical Engineering, July 2008, 25(4), 631-636(6), 10.1007/s11814-008-0105-3

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Abstract

We propose a new system identification method for Hammerstein-Wiener processes, in which an input static nonlinear block, a linear dynamic block, and an output static nonlinear block are connected in a series. The proposed method can estimate the model parameters in a very simple way without solving the full-dimensional nonlinear optimization problem by activating the process with a specially designed test signal, composed of a relay feedback signal, a binary signal and a multi-step signal. The proposed method analytically identifies the output nonlinear static function and the input nonlinear static function from the relay signal and the multi-step signal, respectively. The linear dynamic subsystem is identified from the relay feedback signal and the binary signal with existing well-established linear system identification methods. We demonstrate with a simple example that the proposed method can be successfully applied to identify the Hammerstein-Wiener-type nonlinear process.

Keywords

Relay Feedback Method Identification Test Signal Nonlinearity Hammerstein-Wiener-type Nonlinear Process

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