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AKILLI SİSTEMLER VE UYGULAMALARI DERGİSİ
JOURNAL OF INTELLIGENT SYSTEMS WITH APPLICATIONS
J. Intell. Syst. Appl.
E-ISSN: 2667-6893
Creative Commons License This work is licensed under a Creative Commons Attribution 4.0 International License.

Optimization of Fuzzy Logic Controller by Using Heuristic Algorithms

Sezgisel Algoritmalar Kullanılarak Bulanık Mantık Denetleyici Optimizasyonu

How to cite: Ünsal S, Alışkan . Optimization of fuzzy logic controller by using heuristic algorithms. Akıllı Sistemler ve Uygulamaları Dergisi (Journal of Intelligent Systems with Applications) 2019; 2(1): 13-18. DOI: 10.54856/jiswa.201905052

Full Text: PDF, in Turkish.

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Title: Optimization of Fuzzy Logic Controller by Using Heuristic Algorithms

Abstract: There are many design parameters in the structure of fuzzy logic controllers. Conventional methods that don't have a systematic approach are often used in determining of these parameters. However, setting the controller parameters in this way leads to long experiments and this takes a lot of time. For this reason, design parameters of the fuzzy logic controller are usually determined by using heuristic algorithms. Because, heuristic algorithms can offer solutions that are very close to the optimal solution for the problems where exact solution cannot be obtained. In this study, output membership functions of a fuzzy logic controller are optimized using particle swarm optimization and genetic algorithm. Design and optimization stages are explained in detail and results are compared with each other.

Keywords: Fuzzy logic; genetic algorithm; particle swarm optimization; heuristic algorithms


Başlık: Sezgisel Algoritmalar Kullanılarak Bulanık Mantık Denetleyici Optimizasyonu

Özet: Bulanık mantık denetleyicilerin yapısında birçok tasarım parametresi bulunmaktadır. Bu parametrelerin belirlenmesinde çoğunlukla sistematik bir yaklaşıma sahip olmayan geleneksel yöntemler kullanılmaktadır. Ancak, denetleyici parametrelerinin bu şekilde ayarlanması uzun denemelere yol açmakta ve bu durum oldukça fazla zaman almaktadır. Bu nedenle, bulanık mantık denetleyici tasarım parametrelerinin belirlenmesinde genellikle sezgisel algoritmalardan yararlanılmaktadır. Çünkü; sezgisel algoritmalar kesin çözümün elde edilemediği problemlerde optimum çözümün çok yakınında çözümler sunabilen algoritmalardır. Ele alınan çalışmada, bir bulanık mantık denetleyicinin çıkış üyelik fonksiyonları parçacık sürüsü optimizasyonu ve genetik algoritma kullanılarak optimize edilmiştir. Tasarım ve optimizasyon aşamaları detaylı bir şekilde anlatılarak elde edilen sonuçlar birbiriyle karşılaştırılmıştır.

Anahtar kelimeler: Bulanık mantık; genetik algoritma; parçacık sürüsü optimizasyonu; sezgisel algoritmalar


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