Empirical study of defuzzification

S. S. Lancaster, M. J. Wierman

Research output: Chapter in Book/Report/Conference proceedingConference contribution

17 Citations (Scopus)

Abstract

The most important application of fuzzy logic is designing controllers. Fuzzy logic controllers (FLC) are much easier to design than non-linear controllers of similar capabilities. The rules that a designer needs to create are often based on their current experience and knowledge. Conventional FLCs use Center of Gravity or Mean of Maxima defuzzification methods, though other methods have been studied. This paper compares the efficiency of many different models of the defuzzification process. The goal is to examine the accuracy of the output data and the amount of processing time required. A simple controller that backs a truck up to a gate is used in the study. All of the variables are granulated with trapezoidal fuzzy numbers. Some of the defuzzification methods examined are Fast Center of Gravity, Mean of Maxima, True Center of Gravity and various new methods that have shown promise in application.

Original languageEnglish
Title of host publicationNAFIPS 2003 - 22nd International Conference of the North American Fuzzy Information Processing Society - NAFIPS Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages121-126
Number of pages6
Volume2003-January
ISBN (Electronic)0780379187, 9780780379183
DOIs
StatePublished - 2003
Event22nd International Conference of the North American Fuzzy Information Processing Society, NAFIPS 2003 - Chicago, United States
Duration: Jul 24 2003Jul 26 2003

Other

Other22nd International Conference of the North American Fuzzy Information Processing Society, NAFIPS 2003
CountryUnited States
CityChicago
Period7/24/037/26/03

Fingerprint

Defuzzification
Empirical Study
Centre of gravity
Gravitation
Controllers
Controller
Fuzzy logic
Trapezoidal Fuzzy number
Fuzzy Logic Controller
Trucks
Fuzzy Logic
Output
Processing

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Mathematics(all)

Cite this

Lancaster, S. S., & Wierman, M. J. (2003). Empirical study of defuzzification. In NAFIPS 2003 - 22nd International Conference of the North American Fuzzy Information Processing Society - NAFIPS Proceedings (Vol. 2003-January, pp. 121-126). [1226767] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/NAFIPS.2003.1226767

Empirical study of defuzzification. / Lancaster, S. S.; Wierman, M. J.

NAFIPS 2003 - 22nd International Conference of the North American Fuzzy Information Processing Society - NAFIPS Proceedings. Vol. 2003-January Institute of Electrical and Electronics Engineers Inc., 2003. p. 121-126 1226767.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Lancaster, SS & Wierman, MJ 2003, Empirical study of defuzzification. in NAFIPS 2003 - 22nd International Conference of the North American Fuzzy Information Processing Society - NAFIPS Proceedings. vol. 2003-January, 1226767, Institute of Electrical and Electronics Engineers Inc., pp. 121-126, 22nd International Conference of the North American Fuzzy Information Processing Society, NAFIPS 2003, Chicago, United States, 7/24/03. https://doi.org/10.1109/NAFIPS.2003.1226767
Lancaster SS, Wierman MJ. Empirical study of defuzzification. In NAFIPS 2003 - 22nd International Conference of the North American Fuzzy Information Processing Society - NAFIPS Proceedings. Vol. 2003-January. Institute of Electrical and Electronics Engineers Inc. 2003. p. 121-126. 1226767 https://doi.org/10.1109/NAFIPS.2003.1226767
Lancaster, S. S. ; Wierman, M. J. / Empirical study of defuzzification. NAFIPS 2003 - 22nd International Conference of the North American Fuzzy Information Processing Society - NAFIPS Proceedings. Vol. 2003-January Institute of Electrical and Electronics Engineers Inc., 2003. pp. 121-126
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