Table of Contents Author Guidelines Submit a Manuscript
Mathematical Problems in Engineering
Volume 2013, Article ID 958958, 8 pages
http://dx.doi.org/10.1155/2013/958958
Research Article

Terminal Sliding Mode Control Using Adaptive Fuzzy-Neural Observer

College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China

Received 31 October 2012; Revised 27 December 2012; Accepted 27 December 2012

Academic Editor: Peng Shi

Copyright © 2013 Dezhi Xu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. P. Shi, Y. Xia, G. P. Liu, and D. Rees, “On designing of sliding-mode control for stochastic jump systems,” IEEE Transactions on Automatic Control, vol. 51, no. 1, pp. 97–103, 2006. View at Publisher · View at Google Scholar · View at MathSciNet
  2. J. Zhang, P. Shi, and Y. Xia, “Robust adaptive sliding-mode control for fuzzy systems with mismatched uncertainties,” IEEE Transactions on Fuzzy Systems, vol. 18, no. 4, pp. 700–711, 2010. View at Publisher · View at Google Scholar · View at Scopus
  3. L. Wu, P. Shi, and H. Gao, “State estimation and sliding-mode control of Markovian jump singular systems,” IEEE Transactions on Automatic Control, vol. 55, no. 5, pp. 1213–1219, 2010. View at Publisher · View at Google Scholar · View at MathSciNet
  4. Q. Khan, A. I. Bhatti, M. Iqbal, and Q. Ahmed, “Dynamic integral sliding mode control for SISO uncertain nonlinear systems,” International Journal of Innovative Computing, Information and Control, vol. 8, no. 7, pp. 4621–4633, 2012. View at Google Scholar
  5. L. Wu and D. W. C. Ho, “Sliding mode control of singular stochastic hybrid systems,” Automatica, vol. 46, no. 4, pp. 779–783, 2010. View at Publisher · View at Google Scholar · View at MathSciNet
  6. J. Fei and M. Xin, “Robust adaptive sliding mode controller for semi-active vehicle suspension system,” International Journal of Innovative Computing, Information and Control, vol. 8, no. 1, pp. 691–700, 2012. View at Google Scholar
  7. L. Wu and W. X. Zheng, “Passivity-based sliding mode control of uncertain singular time-delay systems,” Automatica, vol. 45, no. 9, pp. 2120–2127, 2009. View at Publisher · View at Google Scholar · View at MathSciNet
  8. Y. Wu, X. Yu, and Z. Man, “Terminal sliding mode control design for uncertain dynamic systems,” Systems & Control Letters, vol. 34, no. 5, pp. 281–287, 1998. View at Publisher · View at Google Scholar · View at MathSciNet
  9. J. Wang, L. Zou, H. Peng, and G. Zhang, “An extended spiking neural P system for fuzzy knowledge representation,” International Journal of Innovative Computing, Information and Control, vol. 7, no. 7, pp. 3709–3724, 2011. View at Google Scholar · View at Scopus
  10. W. Pawlus, H. R. Karimi, and K. G. Robbersmyr, “Data-based modeling of vehicle collisions by nonlinear autoregressive model and feedforward neural network,” Information Sciences, 2012. View at Publisher · View at Google Scholar
  11. D. Jia and B. You, “Study on novel plasma arc cutting technology based on PIDNN-FUZZY controller,” International Journal of Innovative Computing, Information and Control, vol. 7, no. 7, pp. 4171–4182, 2011. View at Google Scholar · View at Scopus
  12. L. Wu, X. Su, P. Shi, and J. Qiu, “Model approximation for discrete-time state-delay systems in the T–S fuzzy framework,” IEEE Transactions on Fuzzy Systems, vol. 19, no. 2, pp. 366–378, 2011. View at Publisher · View at Google Scholar · View at Scopus
  13. T.-C. Lin, S.-W. Chang, and C.-H. Hsu, “Robust adaptive fuzzy sliding mode control for a class of uncertain discrete-time nonlinear systems,” International Journal of Innovative Computing, Information and Control, vol. 8, no. 1, pp. 347–359, 2012. View at Google Scholar
  14. X. Su, P. Shi, L. Wu, and Y.-D. Song, “A novel approach to filter design for T–S fuzzy discrete-time systems with time-varying delay,” IEEE Transactions on Fuzzy Systems, vol. 20, no. 6, Article ID 6189779, pp. 1114–1129, 2012. View at Publisher · View at Google Scholar
  15. C. M. Lin and C. F. Hsu, “Supervisory recurrent fuzzy neural network control of wing rock for slender delta wings,” IEEE Transactions on Fuzzy Systems, vol. 12, no. 5, pp. 733–742, 2004. View at Publisher · View at Google Scholar · View at Scopus
  16. C. M. Lin and C. F. Hsu, “Supervisory recurrent fuzzy neural network control of wing rock for slender delta wings,” IEEE Transactions on Fuzzy Systems, vol. 12, no. 5, pp. 733–742, 2004. View at Publisher · View at Google Scholar · View at Scopus
  17. B. Jiang, Z. Gao, P. Shi, and Y. Xu, “Adaptive fault-tolerant tracking control of near-space vehicle using TakagiSugeno fuzzy models,” IEEE Transactions on Fuzzy Systems, vol. 18, no. 5, pp. 1000–1007, 2010. View at Publisher · View at Google Scholar · View at Scopus
  18. S. J. Lopez, O. C. Nieto, and J. I. C. Oria, “Non-parametric modeling of uncertain hyperbolic partial differential equations using pseudo-high order sliding mode observers,” International Journal of Innovative Computing, Information and Control, vol. 8, no. 3, pp. 1501–1521, 2012. View at Google Scholar
  19. Y. H. Kim, L. Frank, and C. T. Abdallah, “A dynamic recurrent neural-network-based adaptive observer for a class of nonlinear systems,” Automatica, vol. 33, no. 8, pp. 1539–1543, 1997. View at Publisher · View at Google Scholar · View at MathSciNet
  20. M.-L. Ni and M. J. Er, “Stability of linear systems with delayed perturbations: an LMI approach,” IEEE Transactions on Circuits and Systems. I, vol. 49, no. 1, pp. 108–112, 2002. View at Publisher · View at Google Scholar · View at MathSciNet
  21. S. K. Nguang and P. Shi, “H fuzzy output feedback control design for nonlinear systems: an LMI approach,” IEEE Transactions on Fuzzy Systems, vol. 11, no. 3, pp. 331–340, 2003. View at Publisher · View at Google Scholar · View at Scopus
  22. Y. Wang, T. Chai, and Y. Zhang, “State observer-based adaptive fuzzy output-feedback control for a class of uncertain nonlinear systems,” Information Sciences, vol. 180, no. 24, pp. 5029–5040, 2010. View at Publisher · View at Google Scholar · View at MathSciNet