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Nonlinear Dynamics

, Volume 74, Issue 1–2, pp 21–30 | Cite as

Newton iterative identification for a class of output nonlinear systems with moving average noises

  • Feng Ding
  • Junxia Ma
  • Yongsong Xiao
Original Paper

Abstract

This paper discusses iterative identification problems for a class of output nonlinear systems (i.e., Wiener nonlinear systems) with moving average noises from input–output measurement data, based on the Newton iterative method. The basic idea is to decompose a nonlinear system into two subsystems, to replace the unknown variables in the information vectors with their corresponding estimates at the previous iteration, and to present a Newton iterative identification method using the hierarchical identification principle. The numerical simulation results indicate that the proposed algorithms are effective.

Keywords

Parameter estimation Iterative identification Newton method Nonlinear system 

Notes

Acknowledgements

This work was supported by the National Natural Science Foundation of China (No. 61273194, 61203111), the Natural Science Foundation of Jiangsu Province (China, BK2012549), the Priority Academic Program Development of Jiangsu Higher Education Institutions and the 111 Project (B12018).

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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education)Jiangnan UniversityWuxiP.R. China
  2. 2.Control Science and Engineering Research CenterJiangnan UniversityWuxiP.R. China

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