DECACOPTER BAŞKALAŞIM ETKİSİ ALTINDA BOYLAMASINA UÇUŞUNUN SPSA, SGD VE YSA İLE OPTİMİZASYONUN KARŞILAŞTIRILMASI

Year 2024, Volume: 12 Issue: 3, 539 - 549, 30.09.2024

Oguz Kose , Firat Şal , Tuğrul Oktay

https://doi.org/10.29109/gujsc.1483807

Abstract

İnsansız hava raçları (İHA) üzerine kontrol çalışmaları son yıllarda popülerlik kazanan bir konudur. İHA performansının maksimize edilmesi kontrol alanın temel noktasıdır. İHA grubunda yer alan döner kanatlı İHA’lar rotor sayısına göre isimlendirilir. Bu çalışmada 10 rotora sahip İHA olan decacopter kontrolü ele alınmıştır. Decacopter’in kol uzunlukları değiştirilerek başkalaşım etkisi elde edilmiştir. Simultaneous perturbation stochastic approximation (SPSA) ile kol uzunlukları tahmin edilmiş ve tahmin edilen kol uzunluklarına göre oransal integral türev (PID) katsayıları da tahmin edilerek boylamasına uçuş için kontrol parametreleri elde edilmiştir. Değişen kol uzunluklarına göre atalet momentlerinin tahmini ise stochastic gradient descent (SGD) ve yapay sinir ağları (YSA) ile ayrı ayrı tahmin edilerek boylamasına uçuş simülasyonları yapılmıştır. SGD ve YSA ile eğitim yapılabilmesi veri seti Solidworks çizim programında çizilen modellerden elde edilmiştir. Matlab/Simulink ortamında hem SGD hem de YSA tahminlerine göre boylamasına uçuş simülasyonları yapılmış ve sonuçlar tasarım performans kriterlerine göre karşılaştırılmıştır. Tasarım performans kriterlerine göre YSA ile tahmin edilen parametrelerin SGD’ye göre başkalaşım etkisi altında boylamasına uçuşta daha iyi sonuçlar verdiği gözlemlenmiştir.

Keywords

decacopter, İHA, optimizasyon, SGD, YSA, SPSA

COMPARISON OF THE OPTIMIZATION OF DECACOPTER LONGITUDINAL FLIGHT UNDER THE EFFECT OF MORPHING WITH SPSA, SGD AND YSA

Abstract

Control studies on unmanned aerial vehicles (UAVs) have gained popularity in recent years. Maximising UAV performance is the main point of the control field. Rotary wing UAVs in the UAV group are named according to the number of rotors. In this study, the control of decacopter, a UAV with 10 rotors, is considered. The morphing effect was obtained by changing the arm lengths of the decacopter. Arm lengths are estimated by simultaneous perturbation stochastic approximation (SPSA) and control parameters for longitudinal flight are obtained by estimating proportional integral derivative (PID) coefficients according to the estimated arm lengths. The moments of inertia were estimated separately with stochastic gradient descent (SGD) and artificial neural networks (ANN) and longitudinal flight simulations were performed. The data set for training with SGD and ANN was obtained from the models drawn in Solidworks drawing programme. Longitudinal flight simulations were performed in Matlab/Simulink environment according to both SGD and ANN predictions and the results were compared according to the design performance criteria. According to the design performance criteria, it was observed that the parameters estimated by ANN gave better results in longitudinal flight under the effect of morphnig compared to SGD.

Keywords

decacopter, UAV, optimization, SGD, ANN, SPSA

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