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Reseach Article

Robust Self-Tuning Regulator of Time-Varying Linear Systems with Bounded External Disturbances

by Nabiha Touijer, Samira Kamoun
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 41 - Number 11
Year of Publication: 2012
Authors: Nabiha Touijer, Samira Kamoun
10.5120/5589-7837

Nabiha Touijer, Samira Kamoun . Robust Self-Tuning Regulator of Time-Varying Linear Systems with Bounded External Disturbances. International Journal of Computer Applications. 41, 11 ( March 2012), 44-51. DOI=10.5120/5589-7837

@article{ 10.5120/5589-7837,
author = { Nabiha Touijer, Samira Kamoun },
title = { Robust Self-Tuning Regulator of Time-Varying Linear Systems with Bounded External Disturbances },
journal = { International Journal of Computer Applications },
issue_date = { March 2012 },
volume = { 41 },
number = { 11 },
month = { March },
year = { 2012 },
issn = { 0975-8887 },
pages = { 44-51 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume41/number11/5589-7837/ },
doi = { 10.5120/5589-7837 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:29:21.925319+05:30
%A Nabiha Touijer
%A Samira Kamoun
%T Robust Self-Tuning Regulator of Time-Varying Linear Systems with Bounded External Disturbances
%J International Journal of Computer Applications
%@ 0975-8887
%V 41
%N 11
%P 44-51
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The robust self-tuning regulator of a class of linear systems, which can be described by the input-output Auto-Regressive Moving Average with exogenous (ARMAX) mathematical model with unknown and time-varying parameters, at bounded external disturbances is developed. A scheme of polynomial approximation has been applied to approximate the unknown and time-varying parameters of systems. The modified recursive extended least squares RELS estimation algorithm with a relative dead zone is proposed and applied to estimate the unknown and time-varying parameters intervening in the ARMAX mathematical model. The formulation of the explicit schemes of self-tuning regulation problem is resolved by using the minimum variance output or the generalized minimum variance output. The obtained control law, which is an optimal solution of minimizing a correspondent criterion, permit to reduce the effect of noise upon the output of system. An example of numerical simulation illustrates the effectiveness of the explicit schemes of self-tuning regulator and presents the performances by using the modified recursive extended least squares estimation algorithm with a relative dead zone in a step of the parametric estimation of a linear time-varying systems.

References
  1. Åström K. J. and Wittenmark B. (1973): On self-tuning regulators, Automatica, Vol. 9, pp. 185-199.
  2. Clarke D. W. and Gawthrop P. J. (1979): Self-tuning control. Proceedings of IEE, Vol. 126, pp. 633-640.
  3. Fortescue T. R. , Kershenbaum L. S. and Ydstie B. E. (1981): Implementation of Self Tuning Regulators with Variable Forgetting Factors, Automatica, 27, pp. 831-835.
  4. Goodwin G. C. , Elliot H. and Teoh E. K. (1983): Deterministic convergence of a self-tuning regulator with covariance resetting. IEE Proc. D Control Theory and Appl, 130, pp. 6-8.
  5. Gu X. Y. and Shao C. (1993): Robust adaptive control of time-varying linear plants using polynomial approximation. IEE Proceedings-D, vol. 140, pp. 111-118.
  6. Isermann R. (1984): Process fault detection based on modeling and estimation methods a survey. Automatica, 20(4):pp. 387-404.
  7. Isermann R. (2005): Model-based fault-detection and diagnosis - status and applications. Annual Reviews in Control, 29(1):pp. 71-85.
  8. Jiang J. and Youmin Z. (2004): A revisit to block and recursive least squares for parameter estimation. Computers and Electrical Engineering, 30, 403-416.
  9. Johansson R. (1993): System Modeling and Identification. Prentice Hall, Englewood Cliffs.
  10. Kamoun M. and Titli A. (1988): Parametric identification of large scale discrete time systems. Information and Decision Technologies, Vol. 14, pp. 289-306.
  11. Kamoun S. (2003) : Contribution à l'identification et à la commande adaptative de systèmes complexes. Thesis of doctoral in automatic control. National School of Engineering of Sfax, University of Sfax, 246 pages.
  12. Li Z. (1988): Discrete-time adaptive control for time-varying systems subject to unknown fast time-varying deterministic disturbances, IEE Proc. D, Control theory & Appl. , 135, pp. 445-450.
  13. Li Z. and Evans R. J. (2002): Generalized minimum variance control of linear time-varying systems. IEE Proc. Control Theory Appl. , Vol. 149, pp. 111-116.
  14. Ljung L. and Söderström T. (1983): Theory and Practice of Recursive Identification. MIT Press, Cambridge, Massachusetts.
  15. Maciej N. Z. and Tomasz K. (2001): Fast recursive basis function algorithms for identification of time-varying processes. Proc. IEEE Conf. Decision Contr, 40, pp. 4307-4302.
  16. Ohkawa F. (1986): MRAC for discrete time-varying systems with periodically varying parameters and time delay. Int. J. Control, 44, pp 171-179.
  17. Thil S. (2007): Contributions à l'identification de modèles avec des erreurs en les variables. Thesis of Doctorat, University of Henri Poincaré, Nancy 1.
  18. Toplis B. and Pasupathy S. (1988): Tracking improvements in fast RLS algorithms using a variable forgetting factor. IEEE Trans Acoust Speech Signal Process;ASSP-36(2):206–27.
  19. Tsakalis K. and Ioannou P. A. (1987): Adaptive control of linear time-varying plants. Automatica, 23, pp 459-468.
  20. Van den Hof P. (1996): System identification. Technical Report.
  21. Xianya X. and Evens R. (1984): Discrete-time stochastic adaptive control for time-varying systems. IEEE Trans, AC-29, pp. 638-641.
  22. Xiukun W. , Luigi D. R. and Jindong T. (2005): Robust adaptive control of quasi-LPV systems. Proc. IEEE Conf. Advanced Intelligent Mechatronics. pp. 1617-1622.
  23. Ydstie B. E. (1985): Adaptive Control and Estimation with Forgetting Factors, 7th IFAC Symposium on Identification and System Parameter Estimation, York, July England.
Index Terms

Computer Science
Information Sciences

Keywords

Polynomial Approximation Armax Mathematical Model Time-varying Parameters Modified Recursive Extended Least Squares Estimation Algorithm Rels With A Relative Dead Zone Self-tuning Regulator