Skip to main content
SpringerLink
Log in

Identification of systems with hard input nonlinearities

  • Conference paper
  • First Online:
Perspectives in robust control

Part of the book series: Lecture Notes in Control and Information Sciences ((LNCIS,volume 268))

Abstract

In this paper, we study identification of systems with static and nonstatic hard input nonlinearities. An identification algorithm is proposed which is based on separating the coefficients of the nonlinear part from the linear part. The identification is carried out on an equivalent problem with a much lower dimension. The method is shown to be particularly effective, if the nonlinearity is parametrized by few parameters.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. E.W. Bai (1998), An optimal two-stage identification algorithm for Hammerstein-Wiener nonlinear systems, Automatica, Vol. 34, No. 3. pp.333–338.

    Article  MATH  MathSciNet  Google Scholar 

  2. S.A. Bilings and S.Y. Fakhouri (1978), Identification of a class of nonlinear systems using correlation analysis, Proc. of IEE Vol. 125, No. 7, pp.691–697.

    Google Scholar 

  3. X., Gu, Y. Bao and Z. Lang (1988), A parameter identification method for a class of discrete time nonlinear systems, Proc. 12th IMACS World Congress, Paris, Vil. 4, pp.627–629.

    Google Scholar 

  4. L. Ljung (1976), Consistency of the least squares identification method, IEEE Trans. on Automatic Control, Vol. 21, pp.779–781.

    Article  MATH  MathSciNet  Google Scholar 

  5. A. Ruhe and P. Wedin (1980), Algorithms for separable nonlinear least squares problems, SIAM Review, Vol. 22, pp.318–337.

    Article  MATH  MathSciNet  Google Scholar 

  6. P. Stoica (1981), On the convergence of an iterative algorithm used for Hammerstein system identification, IEEE Trans. on Automatic Control, Vol. 26, pp.967–969.

    Article  MathSciNet  Google Scholar 

  7. G. Tao and C.A. Canudas de Wit (Eds) (1997), SPECIAL ISSUE ON ADAPTIVE SYSTEMS WITH NON-SMOOTH NONLINEARITIES, Int. J. Adapt. Contr. Signal Process, Vol.11, No.1.

    Google Scholar 

  8. G. Tao and P. Kokotovic (1996), ADAPTIVE CONTROL OF SYSTEMS WITH ACTUATOR AND SENSOR NONLINEARITIES, John Wiley and Sons, New York.

    Google Scholar 

  9. J. Voros (1997), Parameter identification of discontinuous Hammerstein systems, Automatic, Vol. 33, No. 6, pp. 1141–1146.

    Article  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Dept. of Electrical and Computer Engineering, University of Iowa, 52242, Iowa City, Iowa

    Er-Wei Bai

Authors
  1. Er-Wei Bai
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

S.O. Reza Moheimani BSc, MengSc, PhD

Rights and permissions

Reprints and permissions

Copyright information

© 2001 Springer-Verlag London Limited

About this paper

Cite this paper

Bai, EW. (2001). Identification of systems with hard input nonlinearities. In: Moheimani, S.R. (eds) Perspectives in robust control. Lecture Notes in Control and Information Sciences, vol 268. Springer, London. https://doi.org/10.1007/BFb0110610

Download citation

  • DOI: https://doi.org/10.1007/BFb0110610

  • Published:

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-85233-452-9

  • Online ISBN: 978-1-84628-576-9

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation