CFP last date
20 January 2025
Reseach Article

Output Feedback Stabilization of a Class of MIMO Uncertain Non-affine Nonlinear Systems

by Zhenfeng Chen, Xuhong Zhang, Zhongsheng Wang
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 124 - Number 17
Year of Publication: 2015
Authors: Zhenfeng Chen, Xuhong Zhang, Zhongsheng Wang
10.5120/ijca2015905777

Zhenfeng Chen, Xuhong Zhang, Zhongsheng Wang . Output Feedback Stabilization of a Class of MIMO Uncertain Non-affine Nonlinear Systems. International Journal of Computer Applications. 124, 17 ( August 2015), 1-5. DOI=10.5120/ijca2015905777

@article{ 10.5120/ijca2015905777,
author = { Zhenfeng Chen, Xuhong Zhang, Zhongsheng Wang },
title = { Output Feedback Stabilization of a Class of MIMO Uncertain Non-affine Nonlinear Systems },
journal = { International Journal of Computer Applications },
issue_date = { August 2015 },
volume = { 124 },
number = { 17 },
month = { August },
year = { 2015 },
issn = { 0975-8887 },
pages = { 1-5 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume124/number17/22196-2015905777/ },
doi = { 10.5120/ijca2015905777 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:14:38.895250+05:30
%A Zhenfeng Chen
%A Xuhong Zhang
%A Zhongsheng Wang
%T Output Feedback Stabilization of a Class of MIMO Uncertain Non-affine Nonlinear Systems
%J International Journal of Computer Applications
%@ 0975-8887
%V 124
%N 17
%P 1-5
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, robust control design is presented for a general class of uncertain non-affine nonlinear systems. The design employs feedback linearization, coupled with two high-gain observers— the first to estimate the feedback linearization error based on the full state information; the second to estimate the unmeasured states of the system when only the system output is available for feedback. All the signals in the closed loop are guaranteed to be uniform ultimate bounded and the output of the system is proven to converge to a small neighborhood of the origin. The proposed approach not only handles the difficulty in controlling non-affine nonlinear systems, but also simplifies the stability analysis of the closed loop due to its simple control structure.

References
  1. Ge, S. S., Hang, C. C., Zhang, T. 1998. Nonlinear adaptive control using neural networks and its application to CSTR systems. Journal of Process Control. 9, 313-323.
  2. Shiriaev, A. S., Ludvigsen, H., Egeland, O., Fradkov, A. L. 1999. Swinging up of non-affine in control pendulum. In: In Proceedings of American Control Conference, San Diego, California, USA, 4039-4044.
  3. Hsu, C. T., Chen, S. L. 2003. Nonlinear control of a 3-pole active magnetic bearing system. Automatica. 39, 291-298.
  4. Chen, Z. F.,Wang, Z. S., Cen, J. 2015. Output feedback stabilization of a class of non-affine nonlinear systems in discrete time. Internatinal Journal of Computer Applications. 119(16), 1-5.
  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, 65–72.
  6. Chen, Z. F., Zhang, X. H., Wang, Z. S. 2015. Direct adaptive control for a class of uncertain nonlinear systems. 119(16), 11-15.
  7. Goh, C. J. 1994. Model reference control of nonlinear systems via implicit funcion emulation. International Journal of Control. 60, 91-115.
  8. Goh, C. J., Lee, T. H. 1994. Direct adaptive control of nonlinear systems via implicit funcion emulation. Control-Theory and Advance Technology. 10 (3), 539-552.
  9. Calise, A. J., Hovakimyan, N., Idan, M. 2001. Adaptive output feedback control of nonlinear systems using neural networks. Automatica. 37, 1201-1211.
  10. Hovakimyan, N., Nardi, F. and 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.
  11. Polycarpou M. M., Ioannou P. A. 1996. A robust adaptive nonlinear control design, Automatica. 32(3), 423-427.
  12. Jiang Z. P. and Praly L. 1998. Design of robust adaptive controllers for nonlinear systems with dynamic uncertainties. Automatica. 34, 825-840.
  13. 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.
  14. Yao B. and Tomizuka M. 1997. Adaptive robust control of SISO nonlinear systems in a semi-strict feedback form. Automatica. 33, 893-900.
Index Terms

Computer Science
Information Sciences

Keywords

Output feedback control multi-input/multi-output (MIMO) nonlinear systems uncertainty