Table of Contents Author Guidelines Submit a Manuscript
Mathematical Problems in Engineering
Volume 2017, Article ID 3597346, 12 pages
https://doi.org/10.1155/2017/3597346
Research Article

Fuzzy Supervisor Approach Design Based-Switching Controller for Pumping Station: Experimental Validation

Higher National Engineering School of Tunis (ENSIT), Laboratory of Industrial Systems Engineering and Renewable Energy (LISIER), University of Tunis, Taha Hussein Street, BP 56, Bab Menara, 1008 Tunis, Tunisia

Correspondence should be addressed to Wael Chakchouk; nt.unr.tisne@kuohckahc.leaw

Received 16 June 2017; Revised 7 September 2017; Accepted 1 November 2017; Published 23 November 2017

Academic Editor: Stefan Balint

Copyright © 2017 Wael Chakchouk 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. S. Vaidyanathan and A. T. Azar, “Takagi-Sugeno fuzzy logic controller for Liu-Chen four-scroll chaotic system,” International Journal of Intelligent Engineering Informatics, vol. 4, no. 2, pp. 135–150, 2016. View at Publisher · View at Google Scholar
  2. D. Lee, Y. H. Joo, and I.-H. Ra, “Local stability and local stabilization of discrete-time T–S fuzzy systems with time-delay,” International Journal of Control, Automation, and Systems, vol. 14, no. 1, pp. 29–38, 2016. View at Publisher · View at Google Scholar · View at Scopus
  3. T. Wang, Y. F. Zhang, J. B. Qiu, and H. J. Gao, “Adaptive fuzzy backstepping control for a class of nonlinear systems with sampled and delayed measurements,” IEEE Transactions on Fuzzy Systems, vol. 23, no. 2, pp. 302–312, 2015. View at Publisher · View at Google Scholar
  4. T. Wang, J. Qiu, S. Fu, and W. Ji, “Distributed Fuzzy filtering for nonlinear multirate networked double-layer industrial processes,” IEEE Transactions on Industrial Electronics, vol. 64, no. 6, pp. 5203–5211, 2017. View at Publisher · View at Google Scholar
  5. T. Takagi and M. Sugeno, “Fuzzy identification of systems and its applications to modeling and control,” IEEE Transactions on Systems, Man, and Cybernetics, vol. 15, no. 1, pp. 116–132, 1985. View at Google Scholar · View at Scopus
  6. T. Wang, J. Qiu, and H. Gao, “Modeling the behavioral substrates of associate learning and memory: adaptive neural models,” IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 21, no. 3, pp. 510–520, 1991. View at Publisher · View at Google Scholar · View at MathSciNet
  7. J. Qiu, S. Ding, H. Gao, and S. Yin, “Fuzzy-model-based reliable static output feedback H-infinity control of nonlinear hyperbolic PDE systems,” IEEE Transactions on Fuzzy Systems, vol. 24, no. 2, pp. 388–400, 2016. View at Publisher · View at Google Scholar
  8. V. H. Grisales, A. Gauthier, and G. Roux, “Fuzzy optimal control design for discrete affine takagi-sugeno fuzzy models: application to a biotechnological process,” in Proceedings of the IEEE World Congress on Computational Intelligence (WCCI '06), pp. 2369–2376, Vancouver, BC, Canada, July 2006. View at Publisher · View at Google Scholar · View at Scopus
  9. J. B. Machado, R. J. G. B. Campello, and W. C. Amaral, “Takagi-Sugeno fuzzy models in the framework of orthonormal basis functions,” IEEE Transactions on Cybernetics, vol. 43, no. 3, pp. 858–870, 2013. View at Publisher · View at Google Scholar · View at Scopus
  10. W.-S. Jang, H.-I. Kang, B.-H. Lee, K. I. Kim, D.-I. Shin, and S.-C. Kim, “Optimized fuzzy clustering by predator prey particle swarm optimization,” in Proceedings of the IEEE Congress on Evolutionary Computation (CEC '07), pp. 3232–3238, Singapore, Singapore, September 2007. View at Publisher · View at Google Scholar · View at Scopus
  11. F. Liu, P. Lu, J. Pan, and R. Pei, “Improved fuzzy identification method based on Hough transformation and fuzzy clustering,” Journal of Systems Engineering and Electronics, vol. 15, no. 3, pp. 257–261, 2004. View at Google Scholar · View at Scopus
  12. C.-F. Juang, C.-M. Hsiao, and C.-H. Hsu, “Hierarchical cluster-based multispecies particle-swarm optimization for fuzzy-system optimization,” IEEE Transactions on Fuzzy Systems, vol. 18, no. 1, pp. 14–26, 2010. View at Publisher · View at Google Scholar · View at Scopus
  13. N. Zahid, O. Abouelala, M. Limouri, and A. Essaid, “Fuzzy clustering based on K-nearest-neighbours rule,” Fuzzy Sets and Systems, vol. 120, no. 2, pp. 239–247, 2001. View at Publisher · View at Google Scholar · View at Scopus
  14. E. Giusti and S. Marsili-Libelli, “A fuzzy decision support system for irrigation and water conservation in agriculture,” Environmental Modeling and Software, vol. 63, pp. 73–86, 2015. View at Publisher · View at Google Scholar · View at Scopus
  15. J. Chrouta, A. Zaafouri, and M. Jemli, “An improved heterogeneous multi-swarm PSO algorithm to generate an optimal T-S fuzzy model of a hydraulic process,” Transactions of the Institute of Measurement and Control, vol. 15, no. 1, Article ID 014233121769634, pp. 1–15, 2017. View at Publisher · View at Google Scholar
  16. M. Soltani, A. Chaari, and F. Ben Hmida, “A novel fuzzy c-regression model algorithm using a new error measure and particle swarm optimization,” International Journal of Applied Mathematics and Computer Science, vol. 22, no. 3, pp. 617–628, 2012. View at Publisher · View at Google Scholar · View at MathSciNet
  17. J. Qin, W. Fu, H. Gao, and W. X. Zheng, “Distributed k-means algorithm and fuzzy c-means algorithm for sensor networks based on multiagent consensus theory,” IEEE Transactions on Cybernetics, vol. 47, no. 3, pp. 772–783, 2017. View at Publisher · View at Google Scholar · View at Scopus
  18. R. Meena Prakash and R. Shantha Selva Kumari, “Spatial fuzzy c means and expectation maximization algorithms with bias correction for segmentation of MR brain images,” Journal of Medical Systems, vol. 41, article 15, 2017. View at Publisher · View at Google Scholar · View at Scopus
  19. W. Chakchouk, A. Zaafouri, and A. Zaafouri, “Modeling, identification and control of irrigation station with sprinkling: Takagi-Sugeno approach,” in Complex System Modelling and Control Through Intelligent Soft Computations, vol. 319 of Studies in Fuzziness and Soft Computing, pp. 469–499, Springer, 2015. View at Publisher · View at Google Scholar · View at Scopus
  20. W. Chakchouk, C. Ben Regaya, A. Zaafouri, and A. Sallami, “An improved fuzzy logic control of irrigation station,” in Proceedings of the International Conference on Control, Decision and Information Technologies (CoDIT '17), Barcelona, Spain, April 2017.
  21. W. Chakchouk, A. Zaafouri, and A. Sallami, “Control and modelling using Takagi-Sugeno fuzzy logic of irrigation station by sprinkling,” World Applied Sciences Journal, vol. 29, no. 10, pp. 1251–1260, 2014. View at Publisher · View at Google Scholar · View at Scopus
  22. M. R. Mejri, A. Zaafouri, and A. Chaari, “Hybrid control of a station of irrigation by sprinkling,” International Journal of Engineering and Innovative Technology, vol. 3, no. 1, pp. 9–17, 2013. View at Google Scholar
  23. W. Chakchouk, A. Zaafouri, and A. Sallami, “Hybrid control of a station of irrigation by sprinkling: fuzzy supervisor approach,” in Proceedings of the 4th International Conference on Systems and Control (ICSC '15), pp. 43–49, Sousse, Tunisia, April 2015. View at Publisher · View at Google Scholar · View at Scopus
  24. L. Wong, F. H. Leung, and P. K. Tam, “Combination of sliding mode controller and pi controller using fuzzy logic controller,” in Proceedings of the IEEE World Congress on Computational Intelligence, Anchorage, Alaska, USA, May 1998. View at Publisher · View at Google Scholar
  25. S.-C. Lin and Y.-Y. Chen, “A GA-based fuzzy controller with sliding mode,” in Proceedings of the Fuzzy Systems, 1995. International Joint Conference of the Fourth IEEE International Conference on Fuzzy Systems and The Second International Fuzzy Engineering Symposium, Yokohama, Japan, March 1995. View at Publisher · View at Google Scholar
  26. F. Barrero, A. González, A. Torralba, E. Galván, and L. G. Franquelo, “Speed control of induction motors using a novel fuzzy sliding-mode structure,” IEEE Transactions on Fuzzy Systems, vol. 10, no. 3, pp. 375–383, 2002. View at Publisher · View at Google Scholar · View at Scopus
  27. M. R. Mejri, A. Zaafouri, and A. Chaari, “Identification and hybrid control of astation of irrigation by sprinkling,” in Proceedings of the 14th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA '13), pp. 1–5, Sousse, Tunisia, December 2013. View at Publisher · View at Google Scholar · View at Scopus
  28. J. Chrouta, A. Zaafouri, M. Jemli, and W. Chakchouk, “Modeling and stabilization of nonlinear systems using PDC approach,” World Applied Sciences Journal, vol. 32, no. 10, pp. 1742–1749, 2014. View at Google Scholar
  29. J. Jantzen, Tuning of Fuzzy PID Controllers, Technical University of Denmark, Department of Automation.
  30. J.-X. Xu, C.-C. Hang, and C. Liu, “Parallel structure and tuning of a fuzzy PID controller,” Automatica, vol. 36, no. 5, pp. 673–684, 2000. View at Publisher · View at Google Scholar · View at Scopus
  31. N. Essounbouli, A. Hamzaoui, and J. Zaytoon, “A supervisory robust adaptive fuzzy controller,” in Proceedings of the 15th Triennial World Congress, pp. 157–162, Barcelona, Spain, July 2002. View at Scopus
  32. N. Essounbouli, A. Hamzaoui, and N. Manamanni, “Fuzzy supervisor for combining sliding mode control and control,” in International Fuzzy Systems Association World Congress, vol. 2715 of Lecture Notes in Computer Science book, pp. 466–473, Springer, Berlin, Germany, 2003. View at Publisher · View at Google Scholar · View at Scopus
  33. N. Essounbouli, N. Manamanni, A. Hamzaoui, and J. Zaytoon, “Synthesis of switching controllers: a fuzzy supervisor approach,” Nonlinear Analysis. Theory, Methods & Applications, vol. 65, no. 9, pp. 1689–1704, 2006. View at Publisher · View at Google Scholar · View at MathSciNet
  34. N. Essounbouli, A. Hamzaoui, and J. Zaytoon, “Fuzzy sliding mode control for a class of non-linear continuous systems,” International Journal of Computer Applications in Technology, vol. 27, no. 2-3, pp. 174–182, 2006. View at Publisher · View at Google Scholar · View at Scopus
  35. F. Xia and Y.-x. Sun, Control and Scheduling Codesign: Flexible Resource Management in Real-Time Control Systems, Advanced Topics in Science and Technology in China, Springer, 2008. View at MathSciNet