İHA Yardımcı İniş Sisteminin Meta-Sezgisel Optimizasyon Yöntemleri ile Kontrolü

Yıl 2021, , 1223 - 1230, 31.10.2021

Serkan Çaşka , Ali Uysal

https://doi.org/10.35414/akufemubid.888652

Cited By: 3

Öz

Dikey iniş/kalkış yapabilen tip insansız hava aracı(İHA) bir zemine inerken, İHA’nın GPS hassasiyetinin düşük olması ve şasisindeki titreşim nedeniyle hedeflenen iniş noktası ile gerçek iniş noktası arasında yatay düzlemde bir miktar hata oluşur. Bu çalışmada, İHA'nın yatay düzlemde iniş yapması sırasında meydana gelen konumlandırma hatasına göre hareket eden bir sistemin kontrolü yapılmıştır. İHA'nın hedef iniş noktasına göre konumunu algılamak için iki dijital kamera içeren bir stereo kamera sistemi kullanılmıştır. İHA'nın gerçek zamanlı konumu, Visual Studio'ya entegre edilmiş olan OpenCV kitaplığı kullanılarak hesaplanmıştır. Elde edilen İHA konumu, yatay düzlemde hareket edebilen bir platformun doğru akım motorları için hedef konum olarak kullanılmıştır. Sistem üzerinde yapılan denemeler kapalı mekanda ve gerçek çalışma koşullarında sağlanmıştır. İniş sistemine entegre edilmiş iki motoru kontrol eden orantı, integral ve türev(PID) tipi denetleyici katsayılarını bulmak için Genetik Algoritma(GA) ve Parçacık Sürüsü Optimizasyonu(PSO) yöntemleri kullanılmıştır. Geliştirilen denetleyicilerin performans sonuçları tablo halinde sunulmuştur.

Anahtar Kelimeler

İnsansız Hava Aracı, Parçacık sürüsü optimizasyonu, Genetik algoritma, PID kontrolör

Control of UAV Auxiliary Landing System with Meta-Heuristic Optimization Methods

Öz

While an unmanned aerial vehicle(UAV) with vertical take off and landing capability is landing onto a ground, a horizontal positioning error occurs between actual landing point and target landing point. This error occurs because of vibration on UAV chasis during flight and low GPS accuracy. In this study, control of an automatic assistive landing system that moves according to the horizontal positioning error that UAV made during its landing was carried out. A stereo camera system with two digital cameras were placed onto a moving platform that UAV lands. Cameras were used to detect actual position of the landing UAV. Real time position of landing UAV was computed by using OpenCV library added into Visual Studio. The calculated position of the landing UAV was defined as target position for two DC motors of moving platform that has horizontal motion capability. The tests of this system were performed in real and indoor conditions. Genetic algorithm (GA) and Particle Swarm Optimization(PSO) algorithm were used to calculate the coefficients of controllers that were defined as Proportional-Integral-Derivative(PID) controllers. Developed controllers control two DC motors of the moving plate of the system. Success of the controllers were compared in table form.

Anahtar Kelimeler

Unmanned Aerial Vehicle, Particle swarm optimization, Genetic algorithm, PID controller

Kaynakça

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