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Self-Tuning Control of a Nonlinear Stochastic Systems Described by a Hammerstein Mathematical Model

by Houda Salhi, Samira Kamoun
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 39 - Number 8
Year of Publication: 2012
Authors: Houda Salhi, Samira Kamoun
10.5120/4839-7101

Houda Salhi, Samira Kamoun . Self-Tuning Control of a Nonlinear Stochastic Systems Described by a Hammerstein Mathematical Model. International Journal of Computer Applications. 39, 8 ( February 2012), 15-22. DOI=10.5120/4839-7101

@article{ 10.5120/4839-7101,
author = { Houda Salhi, Samira Kamoun },
title = { Self-Tuning Control of a Nonlinear Stochastic Systems Described by a Hammerstein Mathematical Model },
journal = { International Journal of Computer Applications },
issue_date = { February 2012 },
volume = { 39 },
number = { 8 },
month = { February },
year = { 2012 },
issn = { 0975-8887 },
pages = { 15-22 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume39/number8/4839-7101/ },
doi = { 10.5120/4839-7101 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:25:54.520604+05:30
%A Houda Salhi
%A Samira Kamoun
%T Self-Tuning Control of a Nonlinear Stochastic Systems Described by a Hammerstein Mathematical Model
%J International Journal of Computer Applications
%@ 0975-8887
%V 39
%N 8
%P 15-22
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, we developed the parametric estimation and the self-tuning control problem of the nonlinear systems which are described by discrete-time nonlinear mathematical models, with unknown, time-varying parameters, and operative in a stochastic environment. The parametric estimation is realized by using the prediction error method and the recursive least squares techniques. The self-tuning control problem is formulated by minimizing a certain quadratic criterion. An example of numerical simulation is treated in this paper, to test the proposed self-tuning control method.

References
  1. Haber, R. and L. Keviczky.1999. Nonlinear System Identification: Input-output Modelling Approach. Kluwer, Boston.
  2. Voros, J.2002. Modeling and parameter identification of systems with multisegment piecewise-linear characteristics. IEEE Transactions on Automatic Control, vol. AC-47, pp. 184-188.
  3. Kamoun, S. 2003. Contribution to the identification and the self-tuning control of complex systems. Thesis of doctorate in Electrical Engineering (Automatic), National Engineering School of Sfax, University of Sfax, Tunisie.
  4. Isermann et al.1992. Adaptive Control Systems. Prentice-Hall, New York.
  5. Salhi, H. 2010. Development of the self-tuning control diagrams of the nonlinear systems. Memory of master in automatic and industrial data processing. National Engineering School of Sfax, University of Sfax, Tunisie..
  6. Oliver Nelles . 2001. Nonlinear system identification. Springer, 2001.
  7. Laurain.V and al. 2008. Refined Instrumental Variable Methods for Hammerstein Box-Jenkins Models. Proceedings of the 47th IEEE Conference on Decision and Control, Cancun, Mexico.
  8. Wang.X and al. 2011. Identification of Hammerstein Models Based on Online Support Vector Regression. Proceedings of the 30th Chinese Control Conference July 22-24, 2011, Yantai, China.
Index Terms

Computer Science
Information Sciences

Keywords

Parametric estimation Discrete-time Hammerstein mathematical model recursive instrumental variable algorithm Self-tuning control

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