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Journal of Applied Mathematics
Volume 2012, Article ID 639014, 22 pages
http://dx.doi.org/10.1155/2012/639014
Research Article

Pareto Design of Decoupled Sliding-Mode Controllers for Nonlinear Systems Based on a Multiobjective Genetic Algorithm

1Department of Mechanical Engineering, Faculty of Engineering, University of Guilan, P.O. Box 3756, Rasht, Iran
2Intelligent-Based Experimental Mechanics Center of Excellence, School of Mechanical Engineering, Faculty of Engineering, University of Tehran, Tehran, Iran
3Department of Mechanical Engineering, Takestan Branch, Islamic Azad University, Takestan, Iran

Received 11 January 2012; Revised 4 April 2012; Accepted 8 April 2012

Academic Editor: Zhiwei Gao

Copyright © 2012 M. J. Mahmoodabadi 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. J. J. E. Slotine and W. Li, Applied Nonlinear Control, Prentice-Hall, Englewood Cliffs, NJ, USA, 1991.
  2. Z. Gao and S. X. Ding, “Actuator fault robust estimation and fault-tolerant control for a class of nonlinear descriptor systems,” Automatica, vol. 43, no. 5, pp. 912–920, 2007. View at Publisher · View at Google Scholar · View at Scopus
  3. Z. Gao, X. Shi, and S. X. Ding, “Fuzzy state/disturbance observer design for T-S fuzzy systems with application to sensor fault estimation,” IEEE Transactions on Systems, Man, and Cybernetics B, vol. 38, no. 3, pp. 875–880, 2008. View at Publisher · View at Google Scholar · View at Scopus
  4. M. J. Mahmoodabadi, A. Bagheri, S. Arabani Mostaghim, and M. Bisheban, “Simulation of stability using Java application for Pareto design of controllers based on a new multi-objective particle swarm optimization,” Mathematical and Computer Modelling, vol. 54, no. 5-6, pp. 1584–1607, 2011. View at Publisher · View at Google Scholar · View at Scopus
  5. J. C. Lo and Y. H. Kuo, “Decoupled fuzzy sliding-mode control,” IEEE Transactions on Fuzzy Systems, vol. 6, no. 3, pp. 426–435, 1998. View at Google Scholar · View at Scopus
  6. A. Bagheri and J. J. Moghaddam, “Decoupled adaptive neuro-fuzzy (DANF) sliding mode control system for a Lorenz chaotic problem,” Expert Systems with Applications, vol. 36, no. 3, pp. 6062–6068, 2009. View at Publisher · View at Google Scholar · View at Scopus
  7. N. H. Moin, A. S. I. Zinober, and P. J. Harley, “Sliding mode control design using genetic algorithms,” in Proceedings of the 1st IEE/IEEE International Conference on Genetic Algorithms in Engineering Systems: Innovations and Applications (GALESIA '95), vol. 414, pp. 238–244, September 1995. View at Scopus
  8. C. C. Wong and S. Y. Chang, “Parameter selection in the sliding mode control design using genetic algorithms,” Tamkang Journal of Science and Engineering, vol. 1, no. 2, pp. 115–122, 1998. View at Google Scholar · View at Scopus
  9. P. C. Chen, C. W. Chen, and W. L. Chiang, “GA-based suzzy sliding mode controller for nonlinear systems,” Mathematical Problems in Engineering, vol. 2008, Article ID 325859, 16 pages, 2008. View at Publisher · View at Google Scholar
  10. J. Javadi-Moghaddam and A. Bagheri, “An adaptive neuro-fuzzy sliding mode based genetic algorithm control system for under water remotely operated vehicle,” Expert Systems with Applications, vol. 37, no. 1, pp. 647–660, 2010. View at Publisher · View at Google Scholar · View at Scopus
  11. H. K. Khalil, Nonlinear Systems, MacMillan, New York, NY, USA, 1992.
  12. N. Yagiz and Y. Hacioglu, “Robust control of a spatial robot using fuzzy sliding modes,” Mathematical and Computer Modelling, vol. 49, no. 1-2, pp. 114–127, 2009. View at Publisher · View at Google Scholar · View at Scopus
  13. W. S. Lin and C. S. Chen, “Robust adaptive sliding mode control using fuzzy modelling for a class of uncertain MIMO nonlinear systems,” IEE Proceedings: Control Theory and Applications, vol. 149, no. 3, pp. 193–202, 2002. View at Publisher · View at Google Scholar · View at Scopus
  14. J. Jing and Q. H. Wuan, “Intelligent sliding mode control algorithm for position tracking servo system,” International Journal of Information Technology, vol. 12, no. 7, pp. 57–62, 2006. View at Google Scholar
  15. V. I. Utkin and H. C. Chang, “Sliding mode control on electro-mechanical systems,” Mathematical Problems in Engineering, vol. 8, no. 4-5, pp. 451–473, 2002. View at Publisher · View at Google Scholar · View at Scopus
  16. N. F. Al-Muthairi and M. Zribi, “Sliding mode control of a magnetic levitation system,” Mathematical Problems in Engineering, vol. 2004, no. 2, pp. 93–107, 2004. View at Publisher · View at Google Scholar · View at Scopus
  17. Z. L. Wan, Y. Y. Hou, T. L. Liao, and J. J. Yan, “Partial finite-time synchronization of switched stochastic Chua's circuits via sliding-mode control,” Mathematical Problems in Engineering, vol. 2011, Article ID 162490, 13 pages, 2011. View at Publisher · View at Google Scholar
  18. C. Pukdeboon, “Optimal sliding mode controllers for attitude stabilization of flexible spacecraft,” Mathematical Problems in Engineering, vol. 2011, Article ID 863092, 20 pages, 2011. View at Publisher · View at Google Scholar
  19. M. Dotoli, P. Lino, and B. Turchiano, “A decoupled fuzzy sliding mode approach to swing-up and stabilize an inverted pendulum, The CSD03,” in Proceedings of the 2nd IFAC Conference on Control Systems Design, pp. 113–120, Bratislava, Slovak Republic, 2003.
  20. J. S. Arora, Introduction to Optimum Design, McGraw-Hill, New York, NY, USA, 1989.
  21. S. S. Rao, Engineering Optimization: Theory and Practice, Wiley, NewYork, NY, USA, 1996.
  22. D. E. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley, Reading, Mass, USA, 1989.
  23. T. Back, D. B. Fogel, and Z. Michalewicz, Handbook of Evolutionary Computation, Institute of Physics Publishing, New York, NY, USA, Oxford University Press, Oxford, UK, 1997.
  24. G. Renner and A. Ekárt, “Genetic algorithms in computer aided design,” Computer Aided Design, vol. 35, no. 8, pp. 709–726, 2003. View at Publisher · View at Google Scholar · View at Scopus
  25. P. J. Fleming and R. C. Purshouse, “Evolutionary algorithms in control systems engineering: a survey,” Control Engineering Practice, vol. 10, no. 11, pp. 1223–1241, 2002. View at Publisher · View at Google Scholar · View at Scopus
  26. C. M. Fonseca and P. J. Fleming, “Multiobjective optimal controller design with genetic algorithms,” in Proceedings of the International Conference on Control, vol. 1, pp. 745–749, March 1994. View at Scopus
  27. G. Sánchez, M. Villasana, and M. Strefezza, “Multi-objective pole placement with evolutionary algorithms,” Lecture Notes in Computer Science, vol. 4403, pp. 417–427, 2007. View at Google Scholar · View at Scopus
  28. E. Alfaro-Cid, E. W. McGookin, D. J. Murray-Smith, and T. I. Fossen, “Genetic algorithms optimisation of decoupled Sliding Mode controllers: simulated and real results,” Control Engineering Practice, vol. 13, no. 6, pp. 739–748, 2005. View at Publisher · View at Google Scholar · View at Scopus
  29. N. Srinivas and K. Deb, “Multiobjective optimization using nondominated sorting in genetic algorithms,” Evolutionary Computation, vol. 2, no. 3, pp. 221–248, 1994. View at Google Scholar
  30. C. M. Fonseca and P. J. Fleming, “Genetic algorithms for multi-objective optimization: formulation, discussion and generalization,” in Proceedings of the 5th International Conference On genetic Algorithms, S. Forrest, Ed., pp. 416–423, Morgan Kaufmann, San Mateo, Calif, USA, 1993.
  31. C. A. Coello and A. D. Christiansen, “Multiobjective optimization of trusses using genetic algorithms,” Computers and Structures, vol. 75, no. 6, pp. 647–660, 2000. View at Publisher · View at Google Scholar · View at Scopus
  32. C. A. Coello Coello, D. A. Van Veldhuizen, and G. B. Lamont, Evolutionary Algorithms for Solving Multi-Objective Problems, Kluwer Academic Publishers, Dordrecht, The Netherlands, 2002.
  33. K. Deb, A. Pratap, S. Agarwal, and T. Meyarivan, “A fast and elitist multiobjective genetic algorithm: NSGA-II,” IEEE Transactions on Evolutionary Computation, vol. 6, no. 2, pp. 182–197, 2002. View at Publisher · View at Google Scholar · View at Scopus
  34. A. Toffolo and E. Benini, “Genetic diversity as an objective in multi-objective evolutionary algorithms,” Evolutionary Computation, vol. 11, no. 2, pp. 151–167, 2003. View at Publisher · View at Google Scholar · View at Scopus
  35. C. A. Coello Coello and R. L. Becerra, “Evolutionary multiobjective optimization using a cultural algorithm,” in Proceedings of the IEEE Swarm Intelligence Symposium, pp. 6–13, IEEE Service Center, Piscataway, NJ, USA, 2003.
  36. K. Atashkari, N. Nariman-Zadeh, A. Pilechi, A. Jamali, and X. Yao, “Thermodynamic Pareto optimization of turbojet engines using multi-objective genetic algorithms,” International Journal of Thermal Sciences, vol. 44, no. 11, pp. 1061–1071, 2005. View at Publisher · View at Google Scholar · View at Scopus