International Journal of Fuzzy Logic and Intelligent Systems

Korean Institute of Intelligent Systems (한국지능시스템학회)
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Intelligent Control of Nonlinear dynamic system Using Immune Fuzzy Fusion

  • Kim, Dong-Hwa (Dept. of Instrumentation and Control Eng., Hanbat National University)
  • Published : 2004.06.01
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Abstract

This paper proposes non-linear control method using immune algorithm based fuzzy logic. Nonlinear dynamic system exist widely in many types of systems such as chemical processes, biomedical processes, and the main steam temperature control system of the thermal power plant. Up to the present time, PID Controllers have been used to operate these systems. However, it is very difficult to achieve an optimal PID gain with no experience, because gain of the PID controller has to be manually tuned by trial and error. An inverted pendulum control problem is selected to illustrate the efficiency of the proposed method and defines relationship state variables $\chi$, $\chi$, $\theta$, $\theta$ using immune fuzzy.

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References

  1. David Lindsley, Boiler Control Systems, McGrawill, 1991
  2. S. Matsummura, Adaptive control for the steam temperature of thermal power plants,' Proceedings the 1993 IEEE on Control applications, PP. 1105 -1109, Sept. 1998
  3. Teng Fong-Chwee, 'Selftuning PID controllers dor dead time process,' IEEE Trans., Vol. 35, No. 1, pp. 119-125, 1988
  4. Ya-Gang Wang, 'PI tuning for processes with dead time,'AACC2000, Chicago, Illinois, June, 2000
  5. B. Stuart, 'Development of PID controller,' IEEE control systems, vol. pp. 58-62, Dec.1993
  6. Y. Stephen, 'A laboratory course on fuzzy control,' IEEE Trans. on Education, vol. 42, no. 1, pp. 15-21, May 1999 https://doi.org/10.1109/13.746327
  7. W. K. Ho, 'PID tuning for unstable process based on gain and phase-margin specifications,' IEE Proc. Control Theory Appl. vol. 45, no. 5, pp. 392-396, Sept. 1998
  8. Assilian and E.H. Mamdani, An experiment in linguistic synthesis with fuzzy logic controllers, Int. J. Man-Machine Studies 7 (1974) 1-13
  9. A. Homaifar and E. Mccormick, Simultaneous design of membership functions and rule sets for fuzzy controllers using genetic algorithms, IEEE Trans. Fuzzy Systems 3(1995) 129-139 https://doi.org/10.1109/91.388168
  10. B. Alfred, 'Neural network-based feedforward control of two-stage heat exchange process,' IEEE conference, pp. 25-29,1997
  11. R. Ketata, D. De Geest and A. Titli, Fuzzy controller: design, evaluation, Parallel and hierarchical combination with a PID controller, Fuzzy Sets and Systems 71 (1995) 113-129 https://doi.org/10.1016/0165-0114(94)00189-E
  12. D. H. Kim, 'A application of intelligent control algorithms,' Conference of ICASE, pp. 15-17, 1997. Seoul
  13. D. H. Kim, 'Application of a multivahable PID controller with a neural network tuning method to the heat exchange,' FUZZ-IEEE, pp. 23-25, Aug.1998, Seoul
  14. Yong Zai Lu, Industrial intelligent control, John Wiley $Sons, 1996
  15. K. J. Astrom, Bjorn Witternmark, Adaptive control, Addison-Wesley Publishing Com., 1995
  16. J. D. Farmer, N. H. Packard and A. S. Perelson, 'The immune system, adaptation, and machine learning, Vol. Physica. D, No. 22, pp. 187 - 204, 1986
  17. Kazuyuki Mori and Makoto Tsukiyama, 'Immune algohthm with searching diversity and its application to resource allocation problem,' Trans. JIEE, Vol. 113 C, No.10, '93
  18. C. V. Rao, An introduction to immunology, 2002, Alpha Science Intemational Ltd
  19. R. Brooks, 'A robust layered control system for a mobile Robot,' IEEE Jounal R&A, vol.2, no.& pp. 14-23, 1986
  20. R. Brooks, 'Intelligence without reason,' Proc. of the UCAI-91,pp.569-595,1991
  21. A. Ishiguro, T. Kondo, Y. Watanabe and Y. Uchikawa, 'Dynamic behavior arbitration of autonomous mobile robots using immune networks,' In Proc. of ICEC' 95, vol.2,pp.722-727,1995
  22. N. K. Jerne, 'The immune system,' Scientific American, vol.229, no.1, pp.52-60,1973 https://doi.org/10.1038/scientificamerican0773-52
  23. N. K. Jerne, 'Idiotypic networks and other preconceived ideas', Immunological Rev., vol.79, pp.5-24, 1984 https://doi.org/10.1111/j.1600-065X.1984.tb00484.x
  24. J. D. Farmer, N. H. Packard and A. S. Perelson, 'The immune system, adaptation, and machine learning,' Physica. D 22, pp.187-204, 1986
  25. F. J. Valera, A. Coutinho, B. Dupire and N. N. Vaz., 'Cognitive networks: Immune, neural, and Otherwise,' Theoretical Immunology, vol.2, pp.359-375, 1988
  26. J. Stewart, 'The immune system: Emergent self-assertion in an autonomous network,' In Proceedings of ECAL-93, pp.1012-1018, 1993
  27. J. D. Farmer, S. A. Kauffman, N. H. Packard and A. S. Perelson, 'Adaptive dynamic networks as models for the immune system and autocatalytic sets,' Technical Report LA-UR-86-3287, Los Alamos National Laboratory, Los Alamos, NM, 1986
  28. K. Nakano, H. Hiraki and S. IKeda, 'A learning machine that evolves,' Proc. of ICEC-95, pp.808-813, 1995
  29. Various Authors, 'Life, death and the immune system,' Scientific American, 269(3), 20-102, 1993 https://doi.org/10.1038/scientificamerican0993-20
  30. S. Forrest, S. A. Hofmeyr, and A. Somayaji, 'Computer immunology,' Communications of the ACM, 40(10):88-96, 1997 https://doi.org/10.1145/262793.262811
  31. D. Gray, 'The dynamics of immunological memory,' Semin. Immunology, 4:29-34, 1992
  32. W. D. Hamilton, R. Axelrod, and R. Tanese, 'Sexual reproduction as an adaptation to resist parasites,' Proceedings of the National Academy of Sciences of the USA, 87:3566-3573, 1990 https://doi.org/10.1073/pnas.87.9.3566
  33. J. K. Inman, 'The antibody combining region: Speculations on the hypothesis of general multispecificity,' Theoretical Immunology, 1978
  34. C. A. Janeway and P. Travers, 'The Immune System in health and disease,' immunobiology, 2nd Edition. Current Biology Ltd., London, 1996
  35. C. A. Janeway and P. Travers, 'The immune system in health and disease,' immunobiology, 3rd Edition. Current Biology Ltd., London, 1996
  36. C. R. MacKay, 'Immunological memory,' Advanced Immunology, 53:217-265, 1993 https://doi.org/10.1016/S0065-2776(08)60501-5
  37. S. Forrest, B. Javornik, R. E. Smith and A. S. Perelson, 'Using genetic algorithms to explore pattern recognition in the immune system,' Evolutionary computation, vol. 1, pp. 191-211, 1993 https://doi.org/10.1162/evco.1993.1.3.191
  38. F. DAlche-Buc, V. Andres and J.P. Nadal, 'Rule extraction with fuzzy neural network,' International J. Neural systems, vol. 5, pp. 1-11, 1994 https://doi.org/10.1142/S0129065794000025
  39. Ishiguro, Y. Watanabe and Y. Uchikawa, 'An hnmunological Approach to dynamic behavior control for autonomous mobile robots,' In Proc. of IROS ' 95, Vol.1, pp.495-500, 1995
  40. D. H. Kim, 'A application of intelligent control algorithms,' Conference of ICASE, pp. 15-17, 1997. Seoul
  41. Dong Hwa Kim, ' 'Tuning of a PID controller using immune network model and fuzzy Set, 'June 15, ISIE2001, Pusan
  42. Dong Hwa Kim, 'Intelligent Tuning of a PID Controller for muldvariable process using immune network model based on fuzzy set,' FUZZ-IEEE2001, Dec. 2-9, 2001, Melbourne, Australia
  43. Dong Hwa Kim, 'A Feasibility Study on Application of Immune Network for Intelligent Controller of a Multivariable System,' ICASE, Jeju, Oct, 17-18, 2001
  44. Dong Hwa Kim, 'Tuning of a PID controller using a artificial immune network model and fuzzy set, 'July 28, IFSA2001, Vancouver
  45. Dong Hwa Kim, 'Parameter tuning of fuzzy neural networks by immune algorithm,' May 12-16, 2002, 2002 TF.F.F. international conference on fiizzy systems, Honolulu, Hawaii, 2002
  46. Dong Hwa Kim, 'Neural networks control by immune algorithm based auto-weight function tuning,' May 12-16, 2002, 2002 IEEE international conference on neural networks, Honolulu, Hawaii, 2002
  47. Dong Hwa Kim, 'Auto-tuning of reference model based PID controller using immune algonthm,' May 12-16, 2002, 2002 IEEE international conference on evolutionary computation, Honolulu, Hawaii, 2002
  48. Dong Hwa Kim, 'Tuning of 2-D0F PID controller by immune algorithm,' May 12-16, 2002, 2002 IEEE international conference on evolutionary computation, Honolulu, Hawaii, 2002
  49. D. H. Kim, 'Intelligent tuning of the two Degrees-of-Freedom Proportional-Integral-Derivative controller on the Distributed control system for steam temperature of thermal power plant,' KIEE international Transaction on SC, Vol. 2-D, No. 2, pp. 78-91, 2002
  50. Wen Tan, Horacio J, Marquez, and Tongwen Chen, 'Multivariable Robust Controller Design for a Boiler System', IEEE Trans. on control systems Technology, Vol. 10, No. 5, Sept. 2002
  51. Yong-Yan Cao, 'Stability analysis ans synthesis of nonlinear time-delay systems via linea Takagi-Sugeno fuzzy models', Fuzzy sets and systems 124, pp. 213-229, 2001 https://doi.org/10.1016/S0165-0114(00)00120-2
  52. Cheng-Sheng Ting, Tzuu-Hseng S. Li, Fan-Chu Kung, 'An approach to systematic of the fuzzy control system', Fuzzy sets and systems 77, pp. 151-166, 1996
  53. Michael Margaliot, Gideon Langholz, 'Fuzzy lynapunovbased approach to the design of fuzzy controllers', Fuzzy sets and systems 106, pp. 49-59, 1999

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