Approximation-based adaptive tracking control of nonlinear pure-feedback systems with time-varying output constraints
详细信息    查看全文
  • 作者:Bong Su Kim (1)
    Sung Jin Yoo (1)

    1. School of Electrical and Electronics Engineering
    ; Chung-Ang University ; 84 Heukseok-ro ; Dongjak-gu ; Seoul ; 156-756 ; Korea
  • 关键词:Dynamic surface design ; function approximation technique ; pure ; feedback systems ; time ; varying output constraint
  • 刊名:International Journal of Control, Automation and Systems
  • 出版年:2015
  • 出版时间:April 2015
  • 年:2015
  • 卷:13
  • 期:2
  • 页码:257-265
  • 全文大小:2,174 KB
  • 参考文献:1. Krstic, M., Kanellakopoulos, I., Kokotovic, P. (1995) Nonlinear and Adaptive Control Design. Hoboken, Wiley, NJ
    2. Swaroop, D., Hedrick, J. K., Yip, P. P., Gerdes, J. C. (2000) Dynamic surface control for a class of nonlinear systems. IEEE Trans. on Automatic Control 45: pp. 1893-1899 CrossRef
    3. Ge, S. S., Wang, C. (2002) Adaptive NN control of uncertain nonlinear pure-feedback systems. Automatica 38: pp. 671-682 CrossRef
    4. Wang, D., Huang, J. (2002) Adaptive neural network control for a class of uncertain nonlinear systems in pure-feedback form. Automatica 38: pp. 1365-1372 CrossRef
    5. Zhang, T. P., Ge, S. S. (2008) Adaptive dynamic surface control of nonlinear systems with unknown dead zone in pure feedback form. Automatica 44: pp. 1895-1903 CrossRef
    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: pp. 723-731 CrossRef
    7. Wang, M., Liu, X., Shi, P. (2011) Adaptive neural control of pure-feedback nonlinear time-delay systems via dynamic surface technique. IEEE Trans. Systems, Man, and Cybernetics 41: pp. 1681-1692 CrossRef
    8. Zhang, T. P., Wen, H., Zhu, Q. (2010) Adaptive fuzzy control of nonlinear systems in pure feedback form based on input-to-state stability. IEEE Trans. on Fuzzy Systems 18: pp. 80-93 CrossRef
    9. Sun, G., Wang, D., Li, X., Peng, Z. (2013) A DSC approach to adaptive neural network tracking control for pure-feedback nonlinear systems. Applied Mathematics and Computation 219: pp. 6224-6235 CrossRef
    10. Allgower, F., Findeisen, R., Ebenbauer, C. (2003) Nonlinear model predictive control. Encyclopedia of Life Support Systems.
    11. Gilbert, E. G., Kolmanovsky, I. (2002) Nonlinear tracking control in the presence of state and control constraints: a generalized reference governor. Automatica 38: pp. 2063-2073 CrossRef
    12. Hu, T., Lin, Z. (2001) Control Systems with Actuator Saturation: Analysis and Design. Birkhauser, Boston, MA CrossRef
    13. Ngo, K. B., Mahony, R., Jiang, Z. P. (2005) Integrator backstepping using barrier functions for systems with multiple state constraints. Proc. 44th IEEE Conf. Decision and Control. pp. 8306-8312 CrossRef
    14. Tee, K. P., Ge, S. S., Tay, E. H. (2009) Barrier Lyapunov Functions for the control of output-constrained nonlinear systems. Automatica 45: pp. 918-927 CrossRef
    15. Han, S. I., Lee, J. M. (2012) Adaptive fuzzy backstepping dynamic surface control for output-constrained non-smooth nonlinear dynamic system. International Journal of Control, Automation and Systems 10: pp. 684-696 CrossRef
    16. Ren, B., Ge, S. S., Tee, K. P., Lee, T. H. (2010) Adaptive neural control for output feedback nonlinear systems using a barrier Lyapunov function. IEEE Trans. on Neural Networks 21: pp. 1339-1345 CrossRef
    17. Tee, K. P., Ge, S. S. (2011) Control of nonlinear systems with partial state constraints using a barrier Lyapunov function. International Journal of Control 84: pp. 2008-2023 CrossRef
    18. Tee, K. P., Ren, B., Ge, S. S. (2011) Control of nonlinear systems with time-varying output constraints. Automatica 47: pp. 2511-2516 CrossRef
    19. Jeffreys, H. (1988) Methods of Mathematical Physics. Cambridge University Press, England
    20. Polycarpou, M. M., Mears, M. J. (1998) Stable adaptive tracking of uncertain systems using nonlinearly parameterized on-line approximators. International Journal of Control 70: pp. 363-384 CrossRef
    21. Lin, F. J., Lee, T. S., Lin, C. H. (2003) Robust H 鈭?controller design with recurrent neural network for linear synchronous motor drive. IEEE Trans. Ind. Electron. 50: pp. 456-470 CrossRef
    22. Ge, S. S., Hang, C. C., Lee, T. H., Zhang, T. (2001) Stable Adaptive Neural Network Control. Kluwer, Norwell, MA
    23. Khalil, H. K. (1996) Nonlinear Systems. Prentice-Hall, Upper Saddle River, NJ
    24. Ioannou, P. A., Kokotovic, P. V. (1983) Adaptive Systems with Reduced Models. Springer-Verlag, NY CrossRef
    25. Yoo, S. J., Park, J. B., Choi, Y. H. (2007) Indirect adaptive control of nonlinear dynamic systems using self-recurrent wavelet neural networks via adaptive learning rates. Information Sciences 177: pp. 3074-3098 CrossRef
  • 刊物类别:Engineering
  • 刊物主题:Control Engineering
  • 出版者:The Institute of Control, Robotics and Systems Engineers and The Korean Institute of Electrical Engi
  • ISSN:2005-4092
文摘
An adaptive neural network control problem of completely non-affine pure-feedback systems with a time-varying output constraint and external disturbances is investigated. For the controller design, we presents an appropriate Barrier Lyapunov Function (BLF) considering both the time-varying output constraint and the control direction nonlinearities induced from the implicit function theorem and mean value theorem. From an error transformation, the BLF dependent on the time-varying constraint is transformed into the explicitly time-independent BLF. Based on the explicitly time-independent BLF, an adaptive dynamic surface control scheme using the function approximation technique is designed to ensure both the constraint satisfaction and the desired tracking ability. It is shown that all signals in the closed-loop system are semi-globally uniformly ultimately bounded and the tracking error converges to an adjustable neighborhood of the origin while the time-varying output constraint is never violated.

© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号

地址:北京市海淀区学院路29号 邮编:100083

电话:办公室:(+86 10)66554848;文献借阅、咨询服务、科技查新:66554700