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Reseach Article

Output Feedback Stabilization of a Class of Non-affine Nonlinear Systems in Discrete Time

by Zhenfeng Chen, Zhongsheng Wang, Jian Cen
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 119 - Number 16
Year of Publication: 2015
Authors: Zhenfeng Chen, Zhongsheng Wang, Jian Cen
10.5120/21148-4167

Zhenfeng Chen, Zhongsheng Wang, Jian Cen . Output Feedback Stabilization of a Class of Non-affine Nonlinear Systems in Discrete Time. International Journal of Computer Applications. 119, 16 ( June 2015), 1-5. DOI=10.5120/21148-4167

@article{ 10.5120/21148-4167,
author = { Zhenfeng Chen, Zhongsheng Wang, Jian Cen },
title = { Output Feedback Stabilization of a Class of Non-affine Nonlinear Systems in Discrete Time },
journal = { International Journal of Computer Applications },
issue_date = { June 2015 },
volume = { 119 },
number = { 16 },
month = { June },
year = { 2015 },
issn = { 0975-8887 },
pages = { 1-5 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume119/number16/21148-4167/ },
doi = { 10.5120/21148-4167 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:04:10.489618+05:30
%A Zhenfeng Chen
%A Zhongsheng Wang
%A Jian Cen
%T Output Feedback Stabilization of a Class of Non-affine Nonlinear Systems in Discrete Time
%J International Journal of Computer Applications
%@ 0975-8887
%V 119
%N 16
%P 1-5
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, output feedback control is investigated for a general class of uncertain non-affine nonlinear systems in discrete time. Control system design employs feedback linearization, coupled with a novel filter which is built to estimate the feedback linearization error. Output feedback control is then developed to stabilize the systems by utilizing the estimation. In the control design, implicit function theorem and the mean value theorem are exploited to handle the difficulty of non-affine appearance of the control input. The proposed control is of great significance in engineering practice due to its linear control architecture, high dynamic performance, clear physical meanings and robustness to the modeling errors.

References
  1. Chen Z. F. , Ge S. S. , Zhang Y. , Li Y. 2014. Adaptive neural control of MIMO nonlinear systems with a block-triangular pure-feedback control structure. IEEE Transactions on Neural Networks and Learning Systems. 25(11), 2017-2029.
  2. Chen Z. F. , Zhang Y. 2014. Robust control of a class of nonaffine nonlinear systems by state and output feedback. Journal of Central South University, 21(4), 1322-1328.
  3. Hsu C. T. , Chen S. L. 2003. Nonlinear control of a 3-pole active magnetic bearing system. Automatica. 39, 291-298.
  4. Ge S. S. , Hang C. C. , Zhang T. 1999. Adaptive neural network control of nonliear systems by state and output feedback. IEEE Transactions on Systems, Man, and Cybernetics- Part B: Cybernetics. 29(6), 818-828.
  5. Park J. H. , Kim S. H. 2004. Direct adaptive output-feedback fuzzy controller for a nonaffine nonlinear system. IEE Proceedings Control Theory and Applications. 51(1), 65-72.
  6. Wang C. , Hill D. J. , Ge S. S. , Chen G. 2006. An ISS-modular approach for adaptive neural control of pure-feedback systems. Automatica. 42, 723-731.
  7. Song Y. , Grizzle J. W. 1993. Adaptive Output-Feedback Control of a Class of Discrete-Time Nonlinear Systems. In Proceedings of American Control Conference. 1359-1364.
  8. Kanellakopoulos I. 1994. A discrete-time adaptive nonlinear system. IEEE Transactions on Automatic Control. 39(11), 2362-2365.
  9. Chen F. C. , Khalil H. K. 1995, Adaptive control of a class of nonlinear discrete-time systems using neural networks. IEEE Transactions on Automatic Control. 40(5), 791C801.
  10. Jagannathan S. , Lewis F. L. 1996. Discrete-time neural net controller for a class of nonlinear dynamical systems. IEEE Transactions on Automatic Control. 41(11), 1693C1699.
  11. Ge S. S. , Li G. Y. , Lee T. H. Adaptive NN control for a class of strict-feedback discrete-time nonlinear systems. Automatica, 39, 807-819.
  12. Ge S. S. , Yang C. , Lee T. H. 2008. Adaptive predictive control using neural network for a class of pure-feedback systems in discrete time. IEEE Transactions on Neural Networks. 19(9), 1599-1614.
  13. Liu Y. J. , Chen P. , Wen G. X. , Tong S. 2011. Adaptive Neural output feedback tracking control for a class of uncertain discrete-time nonlinear systems. IEEE Transactions on Neural Networks. 22(7), 1162-1167.
  14. Ge S. S. , Wang C. 2002. Adpative NN control of uncertain nonlinear pure-feedback systems. Automatica. 38, 671–682.
  15. Shiriaev, A. S. , Ludvigsen, H. , Egeland, O. , Fradkov, A. L. 1999. Swinging up of non-affine in control pendulum. In Proceedings of American Control Conference, San Diego, California, USA, 4039–4044.
  16. Ge S. S. , Lee T. H. , Harris C. J. 1998. Adaptive Neural Network Control of Robotic Manipulators. London, U. K. : World Scientific.
  17. Park J. H. , Huh S. H. , Kim S. H. , Seo S. J. , Park G. T. 2005. Direct adaptive controller for nonaffine nonlinear systems using self-structuring neural networks. IEEE Transactions on Neural Networks. 16(2), 414–422.
  18. Hovakimyan N. , Nardi F. , Calise A. J. 2002. A novel error boserver-based adaptive output feedback aproach for control of uncertain systems. IEEE Transactions on Automatic Control. 47(8), 1310–1314.
Index Terms

Computer Science
Information Sciences

Keywords

Nonaffine nonlinear systems discrete-time systems output feedback control uncertainty