Yapay Sinir Ağları Kullanarak Akıllı Kuadkopter Kontrolü

Bu çalışmada ileri seviyede bir kontrolör mimarisi tasarlanmış ve geliştirilmiştir. Kontrolöre girdi olarak sadece hata sinyali yerine referans ve ölçüm sinyalleri ayrı ayrı girilmiştir. Bu yaklaşım doğrusallıktan yüksek derecede farklı olan kuadkopterin kontrol performansını artırmıştır. Bu çalışmada tek katmanlı sinir ağı doğrudan kontrolör olarak kullanılmıştır. Basitten başlayarak daha karmaşık bir kontrolörü tasarlayarak bir bakıma kontrolör büyütme yapılmıştır. Bu sayede son derece yüksek boyutlu olan parametre uzayında arama zamanı oldukça azaltılmıştır. Literatürdeki mevcut başarılı kontrolörlere göre yüzde on civarında bir performans artışı gözlemlenmiştir. Sonuçlar hem numerik olarak hem de grafiksel olarak verilmiştir. Elde edilen cesaret verici sonuçlar önerilen kontrolör algoritmasının yeni platformlarda da denenmesinin yolunu açacaktır.

Anahtar Kelimeler:

Kuadkopter kontrolü, PSO, tek katmanlı sinir ağı, PID Kontrolör

Intelligent Quadcopter Control Using Artificial Neural Networks

An advanced controller architecture and design for quadcopter control implementation is proposed in this study. Instead of using only the error information as input to the controller, reference and measured outputs are used separately independent from each other. This enhances the performance of the controller of quadcopter being a highly non-linear platform. In this study single layer neural network is directly used as a controller. A complex controller is grown from an initially simple PID controller. This elevates the need for time consuming search in huge parameter space due to very high dimensions. About ten percent improvement over state-of-the-art controllers is observed and results are reported both numerically and graphically. Promising results encourage to use the type of controller proposed for various real applications.

Keywords:

PSO, Quadcopter control, single layer neural network, PID Controller,

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