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Iterative Identification Algorithms for Bilinear-in-parameter Systems by Using the Over-parameterization Model and the Decomposition

  • Mengting Chen
  • Feng Ding
  • Ahmed Alsaedi
  • Tasawar Hayat
Regular Papers Control Theory and Applications
  • 14 Downloads

Abstract

This paper focuses on the identification problem for a class of bilinear-in-parameter systems with an additive noise modeled by an autoregressive moving average process. By using the over-parameterization model, the special form of the bilinear term can be obtained by the model equivalent transformation. Then, we use a decomposition of the model into two synthetic models in order to separate the effect of the two sets of parameters, i.e., the coefficients of the nonlinear basis functions from the parameters of the colored noise. Moreover, two decomposition based iterative algorithms are proposed to identify the unknown parameters. A numerical example is presented to confirm the effectiveness of the proposed methods.

Keywords

Bilinear-in-parameter system decomposition iterative identification over-parameterization parameter estimation 

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Copyright information

© Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Mengting Chen
    • 1
  • Feng Ding
    • 1
    • 2
  • Ahmed Alsaedi
    • 3
  • Tasawar Hayat
    • 3
    • 4
  1. 1.Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), School of Internet of Things EngineeringJiangnan UniversityWuxiP. R. China
  2. 2.College of Automation and Electronic EngineeringQingdao University of Science and TechnologyQingdaoP. R. China
  3. 3.NAAM Research Group, Department of Mathematics, Faculty of ScienceKing Abdulaziz UniversityJeddahSaudi Arabia
  4. 4.Department of MathematicsQuaid-I-Azam UniversityIslamabadPakistan

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