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Soft Computing
Published in: Soft Computing 6/2011

01-06-2011 | Focus

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

Authors: O. Castillo, P. Melin, A. Alanis, O. Montiel, R. Sepulveda

Published in: Soft Computing | Issue 6/2011

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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.
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Metadata
Title
Optimization of interval type-2 fuzzy logic controllers using evolutionary algorithms
Authors
O. Castillo
P. Melin
A. Alanis
O. Montiel
R. Sepulveda
Publication date
01-06-2011
Publisher
Springer-Verlag
Published in
Soft Computing / Issue 6/2011
Print ISSN: 1432-7643
Electronic ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-010-0588-9

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