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Parameter estimation for a special class of nonlinear systems by using the over-parameterisation method and the linear filter

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Listed:
  • Mengting Chen
  • Feng Ding
  • Rongming Lin
  • Ahmed Alsaedi
  • Tasawar Hayat

Abstract

This paper studies the parameter estimation issues of a special class of nonlinear systems (i.e. bilinear-in-parameter systems) utilising the measurement input-output data. The estimation idea is based on the data filtering technique and the over-parameterisation method to represent the system as a linearly parameterised form. Then, by means of the filtered model and the noise model, a filtering based over-parameterisation generalised extended gradient iterative (F-O-GEGI) algorithm is developed for estimating all the parameters. For purpose of improving the precision of parameter estimation, a filtering based over-parameterisation generalised extended least squares iterative (F-O-GELSI) algorithm is derived by formulating and minimising two separate criterion functions. By these foundations, the F-O-GEGI algorithm and the F-O-GELSI algorithm with finite measurement data are presented. The simulation example is provided to test and compare the presented approaches.

Suggested Citation

  • Mengting Chen & Feng Ding & Rongming Lin & Ahmed Alsaedi & Tasawar Hayat, 2019. "Parameter estimation for a special class of nonlinear systems by using the over-parameterisation method and the linear filter," International Journal of Systems Science, Taylor & Francis Journals, vol. 50(9), pages 1689-1702, July.
    • Handle: RePEc:taf:tsysxx:v:50:y:2019:i:9:p:1689-1702
    DOI: 10.1080/00207721.2019.1615576
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