2002Unpublished venueRequires access

Hybrid geno-fuzzy controllers

I. Dumitrache, Cătălin Buiu

Open publisher page 2 citations

Abstract

New methods for designing and analyzing fuzzy controllers are required. Some architectures for integrating genetic algorithms with fuzzy logic controllers, the so called hybrid geno-fuzzy controllers, are introduced and discussed. A new hybrid geno-fuzzy controller based on the algebraic model of the fuzzy controller is proposed. Genetic algorithms are shown to be able to deduce the algebraic model of a simple fuzzy controller used for controlling a truck backer-upper system. The genetic algorithm is further used to tune the coefficients of the deduced algebraic model. The presented results indicate that the hybrid geno-fuzzy controller is superior to a conventional fuzzy controller.

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What this paper is about

New methods for designing and analyzing fuzzy controllers are required. Some architectures for integrating genetic algorithms with fuzzy logic controllers, the so called hybrid geno-fuzzy controllers, are introduced and discussed. A new hybrid geno-fuzzy controller based on the algebraic model of the fuzzy controller is proposed. Genetic algorithms are shown to be able to deduce the algebraic model of a simple fuzzy controller used for controlling a truck backer-upper system. The genetic algorithm is further used to tune the coefficients of the deduced algebraic model. The presented results indicate that the hybrid geno-fuzzy controller is superior to a conventional fuzzy controller.

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Available abstract

New methods for designing and analyzing fuzzy controllers are required. Some architectures for integrating genetic algorithms with fuzzy logic controllers, the so called hybrid geno-fuzzy controllers, are introduced and discussed. A new hybrid geno-fuzzy controller based on the algebraic model of the fuzzy controller is proposed. Genetic algorithms are shown to be able to deduce the algebraic model of a simple fuzzy controller used for controlling a truck backer-upper system. The genetic algorithm is further used to tune the coefficients of the deduced algebraic model. The presented results indicate that the hybrid geno-fuzzy controller is superior to a conventional fuzzy controller.

Key concepts: Fuzzy logic, Controller (irrigation), Control theory (sociology), Neuro-fuzzy, Fuzzy control system, Fuzzy set operations, Computer science, Control engineering

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