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Adaptive output-feedback regulation for nonlinear delayed systems using neural network

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Abstract

A novel adaptive neural network (NN) output-feedback regulation algorithm for a class of nonlinear time-varying time-delay systems is proposed. Both the designed observer and controller are independent of time delay. Different from the existing results, where the upper bounding functions of time-delay terms are assumed to be known, we only use an NN to compensate for all unknown upper bounding functions without that assumption. The proposed design method is proved to be able to guarantee semi-global uniform ultimate boundedness of all the signals in the closed system, and the system output is proved to converge to a small neighborhood of the origin. The simulation results verify the effectiveness of the control scheme.

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References

  1. S. L. Niculescu. Delay Effects on Stability: A Robust Control Approach, Springer-Verlay, London, UK, 2001.

    MATH  Google Scholar 

  2. S. K. Nguang. Robust Stabilization of a Class of Time-delay Nonlinear Systems. IEEE Transactions on Automatic Control, vol. 45, no. 4, pp. 756–762, 2000.

    Article  MATH  MathSciNet  Google Scholar 

  3. Y. S. Fu, Z. H. Tian, S. J. Shi. State Feedback Stabilization for a Class of Stochastic Time-delay Nonlinear Systems. IEEE Transactions on Automatic Control, vol. 48, no. 2, pp. 282–286, 2003.

    Article  MathSciNet  Google Scholar 

  4. S. S. Zhou, G. Feng, S. K. Nguang. Comments on “Robust Stabilization of a Class of Time-delay Nonlinear Systems”. IEEE Transactions on Automatic Control, vol. 47, no. 9, pp. 1586–1586, 2002.

    Article  MathSciNet  Google Scholar 

  5. C. C. Hua, X. P. Guan. Comments on “State Feedback Stabilization for a Class of Stochastic Time-delay Nonlinear Systems”. IEEE Transactions on Automatic Control, vol. 49, no. 7, pp. 1216–1216, 2004.

    Article  MathSciNet  Google Scholar 

  6. X. H. Jiao, T. L. Shen. Adaptive Feedback Control of Nonlinear Time-delay Dystems: The LaSalle-Razumikhin-based Approach. IEEE Transactions on Automatic Control, vol. 50, no. 11, pp. 1909–1913, 2005.

    Article  MathSciNet  Google Scholar 

  7. Y. S. Fu, Z. H. Tian, S. J. Shi. Output Feedback Stabilization for Time-delay Nonlinear Systems. Acta Automatica Sinica, vol. 28, no. 5, pp. 802–805, 2002. (in Chinese)

    MathSciNet  Google Scholar 

  8. Y. S. Fu, Z. H. Tian, S. J. Shi. Output Feedback Stabilization for a Class of Stochastic Time-delay Nonlinear Systems. IEEE Transactions on Automatica Control, vol. 50, no. 6, pp. 847–851, 2005.

    Article  MathSciNet  Google Scholar 

  9. C. C. Hua, X. P Guan, P. Shi. Robust Backstepping Control for a Class of Time Delay Systems. IEEE Transactionsons Automatica Control, vol. 50, no. 6, pp. 894–899, 2005.

    Article  MathSciNet  Google Scholar 

  10. M. M. Polycarpou, M. J. Mears. Stable Adaptive Tracking of Uncertain Systems Using Nonlinearly Parameterized Online Approximators. International Journal of Control, vol. 70, no. 3, pp. 363–384, 1998.

    Article  MATH  MathSciNet  Google Scholar 

  11. T. Zhang, S. S. Ge, C. C. Huang. Adaptive Neural Network Control for Strict-feedback Nonlinear Systems Using Backstepping Design. Automatica, vol. 36, no. 12, pp. 1835–1846, 2000.

    MATH  MathSciNet  Google Scholar 

  12. Y. H. Li. Robust and Adaptive Backstepping Control for Nonlinear Systems Using RBF Neural Networks. IEEE Transactions on Neural Networks, vol. 15, pp. 3, pp. 693-701, 2004.

    Google Scholar 

  13. Y. S. Yang, C. J. Zhou. Adaptive Fuzzy H ∞ Stabilization for Strict-feedback Canonical Nonlinear Systems via Backstepping and Small-gain Approach. IEEE Transactions on Fuzzy Systems, vol. 13, no. 1, pp. 104–114, 2005.

    Article  Google Scholar 

  14. D. Wang, J. Huang. Neural Network-based Adaptive Dynamic Surface Control for a Class of Uncertain Nonlinear Sytems in Strict-feedback Form. IEEE Transactions on Neural Networks, vol. 16, no. 1, pp. 195–202, 2005.

    Article  Google Scholar 

  15. H. B. Du, H. H. Shao, P. J. Yao. Adaptive Neural Network Control for a Class of Low-triangular-structured Nonlinear Systems. IEEE Transactions on Neural Networks, vol. 17 no. 2, pp. 509–514, 2006.

    Article  Google Scholar 

  16. J. Y. Choi, J. A. Farrell. Adaptive Observer Backstepping Control Using Neural Networks. IEEE Transactions on Neural Networks, vol. 12, no. 5, pp. 1103–1113, 2001.

    Article  Google Scholar 

  17. J. Stoev, J. Y. Choi, J. Farrell. Adaptive Control for Output Feedback Nonlinear Systems in the Presence of Modeling Errors. Automatica, vol. 38, no. 10, pp. 1761–1767, 2002.

    Article  MATH  MathSciNet  Google Scholar 

  18. K. Funahashi. On the Approximate Realization of Continuous Mappings by Neural Networks. Neural Networks, vol. 2, no. 1, pp. 183–192, 1989.

    Article  Google Scholar 

  19. K. S. Narendra, K. Parthasarathy. Identification and Control of Dynamic Systems Using Neural Networks. IEEE Transactions on Neural Networks, vol. 1, no. 1, pp. 4–27, 1990.

    Article  Google Scholar 

  20. H. Hong, S. S. Ge, T. H. Lee. Practical Adaptive Neural Control of Nonlinear Systems with Unknown Time Delay. IEEE Transactions on Systems, Man, and Cybernetics — Part B, vol. 35, no. 4, pp. 849–854, 2005.

    Article  Google Scholar 

  21. W. S. Chen, J. M. Li. Adaptive Output Feedback Control for Nonlinear Time-delay Systems Using Neural Networks. Journal of Control Theory and Application, vol. 4, no. 4, pp. 313–320, 2006.

    Article  MATH  Google Scholar 

  22. W. S. Chen, J. M. Li. Adaptive Neural Tracking Control for Unknown Output Feedback Nonlinear Time Delay Systems. Acta Automatica Sinica, vol. 31, no. 5, pp. 799–803, 2005. (in Chinese)

    MathSciNet  Google Scholar 

  23. J. K. Hale, S. M. Lunel. Introduction to Functional Differential Equations, Springer-Verlay, New York, USA, 1993.

    MATH  Google Scholar 

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Authors and Affiliations

  1. Department of Applied Mathematics, Xidian University, Xi’an, 710071, PRC

    Wei-Sheng Chen & Jun-Min Li

Authors
  1. Wei-Sheng Chen
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  2. Jun-Min Li
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Corresponding author

Correspondence to Wei-Sheng Chen.

Additional information

This work was supported by National Natural Science Foundation of China (NSFC) (No. 60374015).

Wei-Sheng Chen received the B. Sc. degree in the Department of Mathematics at Qufu Normal University, Qufu, China, in 2000, and the M. Sc. degree in the Department of Applied Mathematics at Xidian University, Xi’an, China, in 2004. He is currently a Ph. D. candidate in the Department of Applied Mathematics at Xidian University, China.

His research interests include robust and adaptive control, neural network control, nonlinear control, and time-delay control systems.

Jun-Min Li received the B. Sc. andM. Sc. degrees from the Department of Applied Mathematics at Xidian University, China, in 1987 and 1989, respectively, and Ph.D. degree in systems engineering from Xi’an Jiaotong University, Xi’an, China, in 1997. He is currently a professor in the Department of Applied Mathematics at Xidian University, China.

His research interests include robust and adaptive control, optimal control, iterative learning control, and networked control systems.

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Chen, WS., Li, JM. Adaptive output-feedback regulation for nonlinear delayed systems using neural network. Int. J. Autom. Comput. 5, 103–108 (2008). https://doi.org/10.1007/s11633-008-0103-2

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  • DOI: https://doi.org/10.1007/s11633-008-0103-2

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