Sabit kanatlı bir İHA’nın model öngörülü kontrolü için döngüde yazılım simülasyonu

Year 2024, Volume: 13 Issue: 1, 318 - 324, 15.01.2024

Zülfü Kuzu Fatma Yıldız Tascıkaraoglu

https://doi.org/10.28948/ngumuh.1331207

Abstract

Bu çalışmada, bilgisayar tabanlı bir uçuş simülatörü olan X-Plane ile Simulink ortak çalışması yapılarak bir Cessna 172 uçağının rüzgârlı hava koşulları altında hız kontrolü gerçekleştirilmiştir. Trim koşullarında doğrusallaştırılan model için model öngörülü kontrolcü (MPC) geliştirilmiş ve döngüde yazılım (SIL) testleri yapılmıştır. Modele, rüzgâr bozucu etkisi olarak literatürde çok tercih edilen Von Karman rüzgâr türbülans modeli eklenmiştir. Veri iletişimi, gerçek zamanlı bir kullanıcı olan datagram protokolü (UDP) ile sağlanmıştır. Benzetim çalışmalarının sonuçları, literatürdeki PID kontrol tabanlı otopilot geliştirme çalışmalarının sonuçlarıyla karşılaştırılarak incelenmiştir. Buna göre, uçuş kontrol yüzeyleri ve gaz kolu kısıtlarının da dikkate alındığı MPC yöntemiyle kontrol edilen İHA’da, yunuslama stabilitesi korunarak hız referansı değişiklikleri doğru bir şekilde izlenmiştir ve benzeri çalışmalara kıyasla daha başarılı sanal uçuş testleri gerçekleştirildiği görülmüştür.

Keywords

Model Öngörülü Kontrol, Döngüde yazılım simülasyon, X-Plane, İHA

Software-in-the-loop simulation of model predictive control applied to a fixed-wing UAV

Abstract

In this study, the speed control of a Cessna 172 aircraft is carried out under windy weather conditions by combining X-Plane, which is a computer-based flight simulator, with Simulink. Model predictive controller (MPC) is developed for the model linearized under trim conditions and software-in-the-loop (SIL) tests are performed. Von Karman wind turbulence model, which is widely preferred in the literature as a wind disturbance effect, is added to the model. Data communication is provided through a real-time user datagram protocol (UDP). The results of simulation studies are examined by comparing those of PID control-based autopilot development studies in the literature. Accordingly, in the UAV controlled by the MPC method, which also takes into account flight control surfaces and throttle constraints, the speed reference changes are accurately monitored while maintaining pitch stability, and it is observed that more successful virtual flight tests are carried out compared to the similar studies.

Keywords

Model Predictive Control, Software-in-the-loop, X-Plane, UAV

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