Skip to main content
Springer Nature Link
Log in

Impact Study of the Footprint of Uncertainty in Control Applications Based on Interval Type-2 Fuzzy Logic Controllers

  • Chapter
  • First Online:
Fuzzy Logic Augmentation of Neural and Optimization Algorithms: Theoretical Aspects and Real Applications

Part of the book series: Studies in Computational Intelligence ((SCI,volume 749))

  • 1330 Accesses

Abstract

Fuzzy control is one of the most important applications of Fuzzy Logic, and with the emergence of Type-2 Fuzzy Logic, now Type-2 Fuzzy Logic Controllers provide the possibility of consider the uncertainty in the controller design, and these results are very useful for noisy environments and with multiple uncertainty sources. However, it is important to identify the relationship between the FOU and noise robustness, observing the behavior of the IT2 FLC with different FOUs in different uncertainty context. The main goal of this paper is to evaluate the impact of the Footprint of Uncertainty (FOU) in the performance of an Interval Type-2 Fuzzy Logic Controllers (IT2 FLC). The experiments considered two plants, evaluating the performance of the same IT2 FLC by changing only the FOU, evaluated in with different noise levels, this in order to find the controller behavior by the variation of the FOU. In addition, we propose to use a heuristic optimization method based on the behavior knowledge and by adjusting the FOU.

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

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. C.C. Lee, Fuzzy logic in control systems: fuzzy logic controller. I. IEEE Trans. Syst. Man Cybern. 20(2), 404–418 (1990)

    Google Scholar 

  2. J. Ahmed, Z. Salam, An improved perturb and observe (P&O) maximum power point tracking (MPPT) algorithm for higher efficiency. Appl. Energy 150, 97–108 (2015)

    Google Scholar 

  3. L.A. Zadeh, Fuzzy logic = computing with words. IEEE Trans. Fuzzy Syst. 4(2), 103–111 (1996)

    Google Scholar 

  4. E.H. Mamdani, Application of fuzzy algorithms for control of simple dynamic plant. Proc. Inst. Electr. Eng. 121(12), 1585–1588 (1974)

    Google Scholar 

  5. H.O. Wang, K. Tanaka, M.F. Griffin, An approach to fuzzy control of nonlinear systems: stability and design issues. IEEE Trans. Fuzzy Syst. 4(1), 14–23 (1996)

    Google Scholar 

  6. M.S. Masmoudi, N. Krichen, M. Masmoudi, N. Derbel, Fuzzy logic controllers design for omnidirectional mobile robot navigation. Appl. Soft Comput. 49, 901–919 (2016)

    Google Scholar 

  7. J. Liu, W. Zhang, X. Chu, Y. Liu, Fuzzy logic controller for energy savings in a smart LED lighting system considering lighting comfort and daylight. Energy Build. 127, 95–104 (2016)

    Google Scholar 

  8. J.M. Mendel, R.I.B. John, Type-2 fuzzy sets made simple. IEEE Trans. Fuzzy Syst. 10(2), 117–127 (2002)

    Google Scholar 

  9. J.M. Mendel, R.I. John, F. Liu, Interval type-2 fuzzy logic systems made simple. IEEE Trans. Fuzzy Syst. 14(6), 808–821 (2006)

    Google Scholar 

  10. A.D. Torshizi, M.H.F. Zarandi, H. Zakeri, On type-reduction of type-2 fuzzy sets: a review. Appl. Soft Comput. 27, 614–627 (2015)

    Google Scholar 

  11. H. Hagras, Type-2 FLCs: a new generation of fuzzy controllers. IEEE Comput. Intell. Mag. 2(1), 30–43 (2007)

    Google Scholar 

  12. O. Castillo, P. Melin, A review on interval type-2 fuzzy logic applications in intelligent control. Inf. Sci. 279, 615–631 (2014)

    Google Scholar 

  13. M.E. Abdelaal, H.M. Emara, A. Bahgat, Interval type 2 fuzzy sliding mode control with application to inverted pendulum on a cart. IEEE Int. Conf. Ind. Technol. (ICIT) 2013, 100–105 (2013)

    Google Scholar 

  14. U. Farooq, J. Gu, J. Luo, On the interval type-2 fuzzy logic control of ball and plate system. IEEE Int. Conf. Robot. Biomimetics (ROBIO) 2013, 2250–2256 (2013)

    Google Scholar 

  15. R. Sepúlveda, O. Montiel, O. Castillo, P. Melin, Embedding a high speed interval type-2 fuzzy controller for a real plant into an FPGA. Appl. Soft Comput. 12(3), 988–998 (2012)

    Google Scholar 

  16. H. Sahu, R. Ayyagari, Interval fuzzy type-II controller for the level control of a three tank system. IFAC-PapersOnLine 49(1), 561–566 (2016)

    Google Scholar 

  17. I.F. Davoudkhani, M. Akbari, Adaptive speed control of brushless DC (BLDC) motor based on interval type-2 fuzzy logic, in 2016 24th Iranian Conference on Electrical Engineering (ICEE) (2016), pp. 1119–1124

    Google Scholar 

  18. M.A. Sanchez, O. Castillo, J.R. Castro, Generalized type-2 fuzzy systems for controlling a mobile robot and a performance comparison with interval type-2 and type-1 fuzzy systems. Expert Syst. Appl. 42(14), 5904–5914 (2015)

    Google Scholar 

  19. O. Castillo, L. Amador-Angulo, J.R. Castro, M. Garcia-Valdez, A comparative study of type-1 fuzzy logic systems, interval type-2 fuzzy logic systems and generalized type-2 fuzzy logic systems in control problems. Inf. Sci. 354, 257–274 (2016)

    Google Scholar 

  20. J. Gosumbonggot, Maximum power point tracking method using perturb and observe algorithm for small scale DC voltage converter. Proc. Comput. Sci. 86, 421–424 (2016)

    Article  Google Scholar 

  21. H. Bounechba, A. Bouzid, K. Nabti, H. Benalla, Comparison of Perturb & Observe and fuzzy logic in maximum power point tracker for PV systems. Energy Proc. 50, 677–684 (2014)

    Article  Google Scholar 

  22. A. Sombra, F. Valdez, P. Melin, O. Castillo, A new gravitational search algorithm using fuzzy logic to parameter adaptation, in IEEE Congress on Evolutionary Computation (Cancun, Mexico 2013), pp. 1068–1074

    Google Scholar 

  23. F. Valdez, P. Melin, O. Castillo, Evolutionary method combining particle swarm optimization and genetic algorithms using fuzzy logic for decision making, in IEEE International Conference on Fuzzy Systems (2009), pp. 2114–2119

    Google Scholar 

  24. G.M. Mendez, O. Castillo, Interval type-2 TSK fuzzy logic systems using hybrid learning algorithm, in The 14th IEEE International Conference on Fuzzy Systems, 2005 FUZZ’05, pp. 230–235

    Google Scholar 

  25. O. Castillo, P. Melin, Design of intelligent systems with interval type-2 fuzzy logic, in Type-2 Fuzzy Logic: Theory and Applications (2008), pp. 53–76

    Google Scholar 

  26. O. Castillo, P. Melin, E. Ramírez, J. Soria, Hybrid intelligent system for cardiac arrhythmia classification with Fuzzy K-Nearest Neighbors and neural networks combined with a fuzzy system. Expert Syst. Appl. 39(3), 2947–2955

    Google Scholar 

  27. L. Aguilar, P. Melin, O. Castillo, Intelligent control of a stepping motor drive using a hybrid neuro-fuzzy ANFIS approach. Appl. Soft Comput. 3(3), 209–219

    Google Scholar 

  28. P. Melin, O. Castillo, in Modelling, Simulation and Control of Non-linear Dynamical Systems: An Intelligent Approach Using Soft Computing and Fractal Theory (CRC Press, 2001)

    Google Scholar 

  29. P. Melin, C.I. Gonzalez, J.R. Castro, O. Mendoza, O. Castillo, Edge-detection method for image processing based on generalized type-2 fuzzy logic. IEEE Trans. Fuzzy Syst. 22(6), 1515–1525

    Google Scholar 

  30. P. Melin, O. Castillo, Intelligent control of complex electrochemical systems with a neuro-fuzzy-genetic approach. IEEE Trans. Ind. Electron. 48(5), 951–955

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Tijuana Institute of Technology, Tijuana, Mexico

    Emanuel Ontiveros, Patricia Melin & Oscar Castillo

Authors
  1. Emanuel Ontiveros
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Patricia Melin
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Oscar Castillo
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Oscar Castillo .

Editor information

Editors and Affiliations

  1. Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana, Baja California, Mexico

    Oscar Castillo

  2. Division of Graduate Studies and Research , Tijuana Institute of Technology , Tijuana, Baja California, Mexico

    Patricia Melin

  3. Systems Research Institute, Polish Academy of Sciences , Warszawa, Poland

    Janusz Kacprzyk

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Ontiveros, E., Melin, P., Castillo, O. (2018). Impact Study of the Footprint of Uncertainty in Control Applications Based on Interval Type-2 Fuzzy Logic Controllers. In: Castillo, O., Melin, P., Kacprzyk, J. (eds) Fuzzy Logic Augmentation of Neural and Optimization Algorithms: Theoretical Aspects and Real Applications. Studies in Computational Intelligence, vol 749. Springer, Cham. https://doi.org/10.1007/978-3-319-71008-2_15

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-71008-2_15

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-71007-5

  • Online ISBN: 978-3-319-71008-2

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics