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Soft Computing

, Volume 15, Issue 6, pp 1145–1160 | Cite as

Optimization of interval type-2 fuzzy logic controllers using evolutionary algorithms

  • O. Castillo
  • P. Melin
  • A. Alanis
  • O. Montiel
  • R. Sepulveda
Focus

Abstract

A method for designing optimal interval type-2 fuzzy logic controllers using evolutionary algorithms is presented in this paper. Interval type-2 fuzzy controllers can outperform conventional type-1 fuzzy controllers when the problem has a high degree of uncertainty. However, designing interval type-2 fuzzy controllers is more difficult because there are more parameters involved. In this paper, interval type-2 fuzzy systems are approximated with the average of two type-1 fuzzy systems, which has been shown to give good results in control if the type-1 fuzzy systems can be obtained appropriately. An evolutionary algorithm is applied to find the optimal interval type-2 fuzzy system as mentioned above. The human evolutionary model is applied for optimizing the interval type-2 fuzzy controller for a particular non-linear plant and results are compared against an optimal type-1 fuzzy controller. A comparative study of simulation results of the type-2 and type-1 fuzzy controllers, under different noise levels, is also presented. Simulation results show that interval type-2 fuzzy controllers obtained with the evolutionary algorithm outperform type-1 fuzzy controllers.

Keywords

Interval type-2 fuzzy logic Evolutionary algorithms Fuzzy control 

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Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  • O. Castillo
    • 1
  • P. Melin
    • 1
  • A. Alanis
    • 1
  • O. Montiel
    • 2
  • R. Sepulveda
    • 2
  1. 1.Tijuana, Institute of TechnologyTijuanaMexico
  2. 2.Center for Research in Digital Systems, IPNTijuanaMexico

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