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Journals / Havacılık ve Uzay Teknolojileri Dergisi / 2016 / Cilt: 9 - Sayı: 1

MODEL PREDICTIVE KONTROL AND ROBUSTNESS TEST OF THE UNMANNED AERIAL VEHICLE (ZANKA-I) IN VARIOUS TURBULENCE

İNSANSIZ KÜÇÜK BİR HAVA ARACININ (ZANKA-I) FARKLI TÜRBÜLANS ORTAMLARINDA MODEL ÖNGÖRÜLÜ KONTROLÜ VE GÜRBÜZLÜK TESTİ

HARUN ÇELİK
TUĞRUL OKTAY
İLKE TÜRKMEN
Pages
31–42
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

As a result of simulating the model, the robustness of control system is proved

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In this paper, the robust control system is designed by using Model Predictive Control for ZANKA-I which is an unmanned aerial vehicle, and its performance is analyzed.
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Key Findings & Data:In order to design the control system, longitudinal and lateral stability of the vehicle are modeled and converted to longitudinal and lateral state-space model, respectively.
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Conclusion & Impact:As a result of simulating the model, the robustness of control system is proved
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

In this paper, the robust control system is designed by using Model Predictive Control for ZANKA-I which is an unmanned aerial vehicle, and its performance is analyzed. In order to design the control system, longitudinal and lateral stability of the vehicle are modeled and converted to longitudinal and lateral state-space model, respectively. Also, the effects of turbulence on longitudinal and lateral stabilityare parametrically modeled and numerically inserted into the state-space models. As a result of simulating the model, the robustness of control system is proved

Özet

Bu çalışmada insansız hava aracı ZANKA-I için Model Öngörülü Kontrol yöntemi kullanılarak güçlü bir kontrol sistemi tasarlanmış ve performans değerlendirmeleri yapılmıştır. Kontrol sistemi tasarımı için hava aracının uzunlamasına ve yanlamasına olan hareketlerinin matematiksel modelleri çıkarılmış ve durum uzay modeli şeklinde ifade edilmişlerdir. Yine hava aracını uçuş esnasında etkileyecek rüzgâr akışları da matematiksel olarak modellenmiş ve etkileri matematiksel durum uzay modellerine eklenmiştir. Bu şekilde elde edilen yeni modelin benzetimi yapılmış ve neticede, kullanılan kontrol yönteminin performansının çok iyi olduğu ispatlanmıştır

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Cite This Article

ÇELİK, H., OKTAY, T., TÜRKMEN, İ. (2016). MODEL PREDICTIVE KONTROL AND ROBUSTNESS TEST OF THE UNMANNED AERIAL VEHICLE (ZANKA-I) IN VARIOUS TURBULENCE. Havacılık ve Uzay Teknolojileri Dergisi, Cilt: 9 - Sayı: 1, 31–42. https://ajindex.com/articles/165914

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References (1)

  1. Austin, R. (2010). "Unmanned Aircraft Systems: UAVS Design, Development and Deployment" Wiley. [2]Schwager, M., Julian, B.J., Angermann, M., Rus, D., (2011) "Eyes in the sky: Decentralized control for the deployment of robotic camera networks" Proceedings of the IEEE, 99(9), 1541-1561. [3]Hoffmann, G.M., Waslander, S.L., Tomlin, C.J., (2006) "Distributed cooperative search using information-theoretic costs for particle filters, with quadrotor applications" In Proceedings of the AIAA Guidance, Navigation, and Control Conference and Exhibit, 21-24. [4]Michael, N., Shen, S., Mohta, K., Mulgaonkar, Y., Kumar, V., Nagatani, K., Tadokoro, S., (2012) "Collaborative mapping of an earthquake>damaged building via ground and aerial robots" Journal of Field Robotics, 29(5), 832-841. [5]Hoffmann, G., Rajnarayan, D.G., Waslander, S.L., Dostal, D., Jang, J.S., Tomlin, C.J., (2004) "The Stanford testbed of autonomous rotorcraft for multi agent control (STARMAC)" In Digital Avionics Systems Conference, 2004. DASC 04, IEEE, Vol 2, pp. 12-E. [6]How, J.P., Bethke, B., Frank, A., Dale, D., Vian, J., (2008), "Real-time indoor autonomous vehicle test environment" Control Systems, IEEE, 28(2), 51-64.[7]Michael, N., Daniel Mellinger, Quentin Lindsey, and V. Kumar. 2010, "The GRASP multiple micro-UAV testbed" Robotics & Automation Magazine, IEEE, 17 (3):56-65.[8]Huang, A.S., Bachrach, A., Henry, P., Krainin, M., Maturana, D., Fox, D., Roy, N., (2011) "Visual odometry and mapping for autonomous flight using an RGB-D camera" In International Symposium on Robotics Research (ISRR), pp. 1-16.[9]Lupashin, S., Schollig, A., Hehn, M., & D'Andrea, R., (2011), "The Flying Machine Arena as of 2010." In 2011 IEEE International Conference on Robotics and Automation,IEEE, 2970-2971.[10]Meier, L., Tanskanen, P., Heng, L., Lee, G.H., Fraundorfer, F., Pollefeys, M. (2012),"PIXHAWK: A micro aerial vehicle design for autonomous flight using onboard computer vision." Autonomous Robots,33 (1-2), 21-39.[11]Alkowatly, M.T., Becerra, V.M., Holderbaum, W., (2014),"Bioinspired Autonomous Visual Vertical Control of a Quadrotor Unmanned Aerial Vehicle", Journal of Guidance, Control, and Dynamics, 1-14.[12]Albayrak, M., Arısoy, A., (2013), "Dört Rotorlu Hava Aracıİçin Gerçek Zamanda Yapay Sinir Ağlarıİle Kontrolör Tasarımı" Journal of Aeronautics & Space Technologies/Havacilik ve Uzay Teknolojileri Dergisi,6(2).[13]Nodland, D., Zargarzadeh, H., Jagannathan, S., (2013),"Neural network-based optimal adaptive