Ali Egemen TAŞÖREN, Alkım GÖKÇEN, Mehmet Uğur SOYDEMİR, Savaş ŞAHİN

Dikey Kalkış ve İniş Sistemi Modeli için Yapay Sinir Ağı Tabanlı Uyarlanır PID Kontrolör Tasarımı

Çalışmada dikey kalkış ve iniş (VTOL) sistem modelinin eğim açısını kontrol etmek için geliştirilen yapay sinir ağı (YSA) tabanlı uyarlanabilir oransal integral türev (PID) denetleyici algoritması tasarlanmıştır. Uygun geleneksel PID denetleyici parametrelerinin hesaplanılmasında, basamak yanıtı ve titreşim metodu yaygın olarak kullanılan tekniklerdir. Bu yöntemler kapalı döngü sistemi içinde geleneksel PID kontrolör için sabit parametreler bulurlar, ancak kapalı döngü sistemindeki yetersiz izleme hatası performansının en iyi hale getirilmesi mevcut bir problem olarak gösterilebilir. Bu sorunun üstesinden gelmek için, önerilen uyarlanabilir PID denetleyicinin parametreleri bir ileri beslemeli çok katmanlı algılayıcı YSA yardımı ile sağlanabilir. Önerilen kontrolör algoritması, elde edilen uyarlanabilir PID denetleyici parametrelerinin uyarlanabilirliği için devinirlik güncellemeli gradyan inişi yöntemini kullanmaktadır. Önerilen uyarlanabilir PID denetleyici algoritması, MATLAB / Simulink ortamında VTOL sistem modelinin yunuslama açısı için arzu edilen çıkışlar sinüs ve birim basamak sinyalleri anlamında test edilmiştir. Elde edilen sonuçlar, parametreleri Simulink PID ayarlayıcı uygulaması ile hesaplanmış geleneksel PID denetleyici ile ortalama kare hata, integral mutlak hata, oturma süresi ve aşım yüzdesi açısından karşılaştırılır.

Anahtar Kelimeler:

VTOL sistemi, Yapay Sinir Ağları, Uyarlanabilir PID kontrolör

Artificial Neural Network-Based Adaptive PID Controller Design for Vertical Takeoff and Landing Model

This study presents an artificial neural network (ANN) based adaptive proportional integral derivative (PID) controller algorithm which is developed to control the pitch angle of the vertical takeoff and landing (VTOL) system model. To find appropriate conventional PID controller parameters, either step response or vibration method might be used in a way of the widely used approach. They provide constant values for the conventional PID controller parameters for a closed-loop system however it is obvious that the unsatisfied tracking error performances in the closed-loop system might be addressed as a problem to be optimized. To overcome this problem, the parameters of the proposed adaptive PID controller might be determined with an ANN constructed feedforward multilayer perceptron. The proposed controller algorithm possesses the gradient descent with momentum update rule for the adaptiveness of the obtained PID parameters. The proposed adaptive PID controller algorithm is tested for the pitch angle of the VTOL system model in the MATLAB/Simulink environment in terms of the sinusoidal and step signals as the desired outputs. The obtained results are compared to the conventional PID controller whose parameters are tuned by Simulink PID tuner application in terms of mean square error, integral absolute error, the settling time, and the percentage overshoot.

Keywords:

VTOL system, Artificial Neural Networks, Adaptive PID controller,

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