Research Article
Self-Tuning Control of a Nonlinear Stochastic Systems Described by a Hammerstein Mathematical Model
|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 39 - Issue 8 |
| Published: February 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 },
year = { 2012 },
volume = { 39 },
number = { 8 },
pages = { 15-22 },
doi = { 10.5120/4839-7101 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2012
%A Houda Salhi
%A Samira Kamoun
%T Self-Tuning Control of a Nonlinear Stochastic Systems Described by a Hammerstein Mathematical Model%T
%J International Journal of Computer Applications
%V 39
%N 8
%P 15-22
%R 10.5120/4839-7101
%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
- Haber, R. and L. Keviczky.1999. Nonlinear System Identification: Input-output Modelling Approach. Kluwer, Boston.
- 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.
- 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.
- Isermann et al.1992. Adaptive Control Systems. Prentice-Hall, New York.
- 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..
- Oliver Nelles . 2001. Nonlinear system identification. Springer, 2001.
- 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.
- 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
Keywords