Skip to main content

Fuzzy Controller Design III: Hybrid Adaptive Approaches

  • Chapter
  • First Online:
Intelligent Control

Part of the book series: Cognitive Intelligence and Robotics ((CIR))

  • 828 Accesses

Abstract

In this chapter, an interesting, contemporary approach for designing stable adaptive fuzzy controllers is described, which employs a hybridization.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 139.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 179.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 179.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. L.-X. Wang, Adaptive Fuzzy Systems and Control: Design and Stability Analysis (Prentice-Hall, Englewood Cliffs, NJ, 1994)

    Google Scholar 

  2. K. Das Sharma, Hybrid Methodologies for Stable Adaptive Fuzzy Control, Doctoral Dissertation, Jadavpur University, India, 2012

    Google Scholar 

  3. F. Cupertino, E. Mininno, D. Naso, B. Turchiano, L. Salvatore, On-line genetic design of anti-windup unstructured controllers for electric drives with variable load. IEEE Trans. Evol. Comput. 8(4), 347–364 (2004)

    Article  Google Scholar 

  4. K. Das Sharma, A. Chatterjee, A. Rakshit, A hybrid approach for design of stable adaptive fuzzy controllers employing Lyapunov theory and particle swarm optimization. IEEE Trans. Fuzzy Syst. 17(2), 329–342 (2009)

    Article  Google Scholar 

  5. K. Das Sharma, A. Chatterjee, A. Rakshit, Harmony search algorithm and Lyapunov theory based hybrid adaptive fuzzy controller for temperature control of air heater system with transport-delay. Appl. Soft Comput. 25, 40–50, Dec (2014)

    Google Scholar 

  6. K. Fischle, D. Schroder, An improved stable adaptive fuzzy control method. IEEE Trans. Fuzzy Syst. 7(1), 27–40 (1999)

    Article  Google Scholar 

  7. K. Das Sharma, A. Chatterjee, F. Matsuno, A Lyapunov theory and stochastic optimization based stable adaptive fuzzy control methodology, in Proceedings of SICE Annual Conference 2008, Japan, 20–22 Aug, pp. 1839–1844

    Google Scholar 

  8. K. Das Sharma, A. Chatterjee, A. Rakshit, Design of a hybrid stable adaptive fuzzy controller employing Lyapunov theory and harmony search algorithm. IEEE Trans. Contr. Syst. Technol. 18(6), 1440–1447, Nov (2010)

    Google Scholar 

  9. R.C. Eberhart, J. Kennedy, A new optimizer using particle swarm theory, in Proceedings of the 6th International Symposium on Micro Machine and Human Science, Nagoya, Japan, 1995, pp. 39–43

    Google Scholar 

  10. J. Kennedy, R.C. Eberhart, Particle swarm optimization. Proc. IEEE Int. Conf. Neural Netw. 4, 1942–1948 (1995)

    Article  Google Scholar 

  11. G. Venter, J.S. Sobieski, Particle swarm optimization, in 43rd AIAA Conference, Colorado, 2002

    Google Scholar 

  12. Y. Shi, R.C. Eberhart, A modified particle swarm optimizer, in Proceedings of the IEEE International Conference on Evolutionary Computation, Alaska, May, 1998

    Google Scholar 

  13. Z.W. Geem, J.H. Kim, G.V. Loganathan, A new heuristic optimization algorithm: harmony search. Simulation 76(2), 60–68 (2001)

    Article  Google Scholar 

  14. K.S. Lee, Z.W. Geem, A new structural optimization method based on the harmony search algorithm. Comput. Struct. 82, 781–798 (2004)

    Article  Google Scholar 

  15. M. Mahdavi, M. Fesanghary, E. Damangir, An improved harmony search algorithm for solving optimization problems. Appl. Math. Comput. 188, 1567–1679 (2007)

    MathSciNet  MATH  Google Scholar 

  16. S.H. Zak, Systems and Control (Oxford University Press, New York, 2003)

    Google Scholar 

  17. C.-T. Chen, Control System Design, Orlando (Saunders College Publishing, Florida, 1993)

    Google Scholar 

  18. D. Driankov, H. Hellendoorn, M.M. Reinfrank, An Introduction to Fuzzy Control (Springer-Verlag, Heidelberg, Germany, 1993)

    Book  Google Scholar 

  19. K.M. Passino, S. Yurkovich, Fuzzy control, in Handbook on Control, ed. by W. Levine (CRC, Boca Raton, FL, 1996), pp. 1001–1017

    Google Scholar 

  20. D. Chakroborty, K. Das Sharma, A study on the design methodologies of fuzzy logic controller, in Proceedings of 17th State Science & Technology Congress, WBUAFS, Kolkata, India, March 2010, p. 69

    Google Scholar 

  21. L.X. Wang, Stable adaptive fuzzy control of nonlinear system. IEEE Trans. Fuzzy Syst. 1(2), 146–155, May (1993)

    Google Scholar 

  22. K. Das Sharma, Stable fuzzy controller design employing group improvisation based harmony search algorithm. Int. J. Contr. Autom. Syst. 11(5), 1046–1052 (2013), Springer

    Google Scholar 

  23. A. Roy, K. Das Sharma, GA and Lyapunov theory based hybrid adaptive fuzzy controller for nonlinear systems. Int. J. Electron. 120(2), 312–325 (2015), Taylor & Francis

    Google Scholar 

  24. D.E. Goldberg, Genetic Algorithms in Search, Optimization and Machine Learning (Kluwer Academic Publishers, Boston, 1989)

    MATH  Google Scholar 

  25. A. Auger, N. Hansen, A restart CMA evolution strategy with increasing population size. Cong. Evol. Comp. 2, 1769–1776 (2005)

    Google Scholar 

  26. E. Rashedi, H. Nezamabadi-pour, S. Saryazdi, GSA: a gravitational search algorithm. Inf. Sci. 179(13), 2232–2248 (2009)

    Article  Google Scholar 

  27. A. Roy, K. Das Sharma, Gravitational search algorithm and Lyapunov theory based stable adaptive fuzzy logic controller, in Proceedings of 1st International Conference on Computational Intelligence: Modelling, Techniques and Applications (CIMTA-2013), Procedia Technol. 10, 581–586 (2013), Elsevier

    Google Scholar 

  28. K.M. Passino, Biomimicry of bacterial foraging for distributed optimization and control, in IEEE Control Systems Magazine, 2002, pp. 52–67

    Google Scholar 

  29. R. Toscano, P. Lyonnet, Stabilization of systems by static output feedback via heuristic Kalman algorithm. J. Appl. Comput. Math. 5(2), 154–165 (2006)

    MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Kaushik Das Sharma .

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Nature Singapore Pte Ltd.

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Das Sharma, K., Chatterjee, A., Rakshit, A. (2018). Fuzzy Controller Design III: Hybrid Adaptive Approaches. In: Intelligent Control . Cognitive Intelligence and Robotics. Springer, Singapore. https://doi.org/10.1007/978-981-13-1298-4_5

Download citation

  • DOI: https://doi.org/10.1007/978-981-13-1298-4_5

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-1297-7

  • Online ISBN: 978-981-13-1298-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics