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Soft Computing

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22.09.2016 | Methodologies and Application

A new fuzzy bee colony optimization with dynamic adaptation of parameters using interval type-2 fuzzy logic for tuning fuzzy controllers

verfasst von: Leticia Amador-Angulo, Oscar Castillo

Erschienen in: Soft Computing | Ausgabe 2/2018

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Abstract

This paper presents a new fuzzy bee colony optimization method to find the optimal distribution of the membership functions in the design of fuzzy controllers for complex nonlinear plants. We used interval type-2 and type-1 fuzzy logic systems in dynamically adapting the alpha and beta parameter values of the bee colony optimization algorithm (BCO). Simulation results with a type-1 fuzzy logic controller for benchmark control plants are presented. The advantage of using interval type-2 fuzzy logic systems for dynamic adjustment of parameters in BCO applied in fuzzy controller design is verified with two benchmark problems. We considered different levels and types of noise in the simulations to analyze the approach of interval type-2 fuzzy logic systems to find the best values of alpha and beta for BCO when applied in the design of fuzzy controllers.

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Titel: A new fuzzy bee colony optimization with dynamic adaptation of parameters using interval type-2 fuzzy logic for tuning fuzzy controllers
verfasst von: Leticia Amador-Angulo
Oscar Castillo
Publikationsdatum: 22.09.2016
Verlag: Springer Berlin Heidelberg
Erschienen in: Soft Computing / Ausgabe 2/2018
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-016-2354-0

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