Multi-Parameter Optimization of Sliding-Mode Controller for Quadcopter Application

Öz

For many years, quadcopters are quite popular in the academic field because of its structural simplicity. However, this property comes out the problem of designing an effective controller. Designing a controller for quadcopter is rather complicated because tuning of the controller parameters of multi-rotor structure to achieve a desired performance for agility, flying efficiency and immediate reaction is a challenging problem. To deal with such a difficulty, Ant Colony Optimization (ACO), Invasive Weed Optimization (IWO) and Firefly Optimization (FO) algorithms are used to obtain optimal parameters of Sliding Mode Controller (SMC). SMC is used for both attitude and position control of the quadcopter. By taking into consideration all six variables with different number of parameters (total number of parameters to be optimized are nineteen). This makes it a complicated tuning problem. In this numerical study, performance results of optimization algorithms are compared with respect to convergence rate and cost function.

Anahtar Kelimeler

• quadcopter,ant colony optimization,firefly optimization,invasive weed optimization,sliding mode control

Quadcopter Uygulamaları için Kayma Kipli Kontrolörün Çok Parametreli Optimizasyonu

Öz

Uzun yıllardan beri, quadcopterler, yapısal sadeliği nedeniyle akademik alanda oldukça popülerdir. Ancak, bu özellik etkili bir denetleyici tasarlama sorununu ortaya çıkarmaktadır. Quadcopter için bir kontrolör tasarlamak oldukça karmaşıktır çünkü çok rotorlu yapının kontrolör parametrelerinin ayarlanması, çeviklik, uçuş verimliliği ve anlık reaksiyon için istenen performansı sağlamak bakımından zor bir problemdir. Böyle bir zorlukla başa çıkmak için, Karınca Koloni Optimizasyonu (ACO), Yayılmacı Yosun Optimizasyonu (IWO) ve Ateş Böceği Optimizasyonu (FO) algoritmaları, kayma kipli kontrolörün (SMC) optimal parametrelerini elde etmek için uygulanmıştır. SMC, quadcopter'in hem durumsal hem de pozisyon kontrolü için çift katmanlı olarak tasarlanıp kullanılmıştır. Farklı sayıda parametreye sahip altı değişkenin hesaba katılmasıyla optimize edilecek toplam parametre sayısı on dokuz olmuştur. Bu da karmaşık bir ince ayarlama problemini ortaya çıkartmaktadır. Bu sayısal çalışmada, optimizasyon algoritmalarının performans sonuçları, yakınsama oranı ve maliyet fonksiyonuna göre karşılaştırmalı olarak sunulmuştur.

Anahtar Kelimeler

• quadcopter,karınca kolonisi optimizasyonu,ateş böceği optimizasyonu,yayılmacı yusun optimizasyonu,kayma kipli kontrol

Kaynakça

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