Nonlinear State Space Modeling and System Identification for Electrohydraulic ControlReport as inadecuate




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Mathematical Problems in EngineeringVolume 2013 2013, Article ID 973903, 9 pages

Research ArticleCollege of Field Engineering, PLA University of Science and Technology, Nanjing 210007, China

Received 6 January 2013; Accepted 29 January 2013

Academic Editor: Shengyong Chen

Copyright © 2013 Jun Yan et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The paper deals with nonlinear modeling and identification of an electrohydraulic control system for improving its tracking performance. We build the nonlinear state space model for analyzing the highly nonlinear system and then develop a Hammerstein-Wiener H-W model which consists of a static input nonlinear block with two-segment polynomial nonlinearities, a linear time-invariant dynamic block, and a static output nonlinear block with single polynomial nonlinearity to describe it. We simplify the H-W model into a linear-in-parameters structure by using the key term separation principle and then use a modified recursive least square method with iterative estimation of internal variables to identify all the unknown parameters simultaneously. It is found that the proposed H-W model approximates the actual system better than the independent Hammerstein, Wiener, and ARX models. The prediction error of the H-W model is about 13%, 54%, and 58% less than the Hammerstein, Wiener, and ARX models, respectively.





Author: Jun Yan, Bo Li, Hai-Feng Ling, Hai-Song Chen, and Mei-Jun Zhang

Source: https://www.hindawi.com/



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