Sabit Kanatlı İHA'ların Boylamasına Kararlılığının Artırılması: Türbülanslı Koşullarda PID Kontrol ve SPSA Optimizasyonunu Kullanan Hibrit Bir Yaklaşım

Abstract

Bu çalışma, sabit kanatlı insansız hava araçlarının (İHA) boylamasına kararlılığını iyileştirmek amacıyla yenilikçi bir yöntem ortaya koymaktadır. Kullanılan yaklaşımda, durum uzay modeli, PID kontrolcüsü ve SPSA (Simultaneous Perturbation Stochastic Approximation) algoritması bir araya getirilmiştir. Sistemin performansı, gerçek dünya koşullarını simüle eden Von Karman türbülans modeli altında test edilmiş ve dikkat çekici sonuçlar elde edilmiştir. Simülasyonlar, önerilen kontrol yönteminin referans açı takibini başarıyla gerçekleştirdiğini ve aynı zamanda aşım ile kararlılık süresini minimize ederek türbülanslı hava koşullarında dahi etkili bir denge sağladığını göstermektedir. Özellikle SPSA algoritması, maliyet fonksiyonunu hızlı bir şekilde optimize ederek kontrol parametrelerini uyarlamış ve sistemin genel performansını önemli ölçüde artırmıştır. Çalışma, değişken çevresel faktörler altında sabit kanatlı İhaların kararlılığını artırmak için pratik ve güçlü bir çözüm sunmaktadır.

Keywords

• İHA
• PİD
• SPSA
• Von Karman

Enhancing Longitudinal Stability of Fixed-Wing UAVs A Hybrid Approach Using PID Control and SPSA Optimization under Turbulent Conditions

Abstract

This study presents an innovative method to enhance the longitudinal stability of fixed-wing unmanned aerial vehicles (UAVs). The proposed approach combines a state-space model, a PID controller, and the Simultaneous Perturbation Stochastic Approximation (SPSA) algorithm to achieve robust and reliable performance. The system's effectiveness was evaluated under realistic conditions using the Von Karman turbulence model, which simulates the challenges posed by varying environmental factors. The results demonstrate that the proposed control method successfully tracks reference angles while minimizing overshoot and settling time, even in turbulent conditions. The SPSA algorithm plays a crucial role in this process by efficiently optimizing the control parameters through cost function minimization, significantly enhancing overall system performance. This method provides a practical and robust solution for improving the longitudinal stability of fixed-wing UAVs, even in dynamic and unpredictable environments.

Keywords

• UAV
• PID
• SPSA
• Von Karman

References

1. Çoban S., Bilgiç HH., Oktay T. Designing, dynamic modeling and simulation of ISTECOPTER. Journal of Aviation 2019; 3(1): 38-44.
2. Çoban S., Oktay T. Simultaneous design of a small UAV (unmanned aerial vehicle) flight control system and lateral state space model. Journal of Aviation 2018; 2(2): 70-76.
3. Hajiyev C., Vural SY. LQR controller with Kalman estimator applied to UAV longitudinal dynamics. Positioning 2013; 4(1): 36-41.
4. He Y., Fu MC., Marcus SI. Convergence of simultaneous perturbation stochastic approximation for non-differentiable optimization. IEEE Transactions on Aerospace and Electronic Systems 2003; 48(8): 1459-1463.
5. Jang JS., Liccardo D. Automation of small UAVs using a low-cost MEMS sensor and embedded computing platform. Proceedings of the IEEE Aerospace Conference 2006; Big Sky, MT, USA.
6. Kocamer A., Oktay T. A novel morphing approach tilt-rotor VTOL UAV. Research and Reviews in Engineering 2022; 11.
7. Muslimov T., Munasypov R. Consensus-based cooperative control of parallel fixed-wing UAV formations via adaptive backstepping. Aerospace Science and Technology 2021; 109: 106416.
8. Nelson RC. Flight stability and automatic control (2nd ed.). McGraw-Hill, New York 2007.

9. Oktay T. Constrained control of complex helicopter models. PhD Dissertation, Virginia Tech, Blacksburg, VA 2012.
10. Oktay T., Sal F., Kose O., Kocamer A. Stochastic longitudinal autopilot tuning for best autonomous flight performance of a morphing VTOL drone. The Eurasia Proceedings of Science Technology Engineering and Mathematics 2023; 23: 413-419.
11. Oktay T., Sultan C. Flight control energy saving via helicopter rotor active morphing. AIAA Journal of Aircraft 2014; 51(6): 1784-1805.
12. Oktay T., Sultan C. Integrated maneuvering helicopter model and controller design. AIAA Guidance, Navigation and Control Conference 2012; Minneapolis, MN, USA.
13. Sadegh P., Spall JC. Optimal random perturbations for multivariable stochastic approximation using a simultaneous perturbation gradient approximation. IEEE Transactions on Automatic Control 1998; 43(10): 1480-1484.
14. Yu L., He G., Wang X., Zhao S. Robust fixed-time sliding mode attitude control of tilt trirotor UAV in helicopter mode. IEEE Transactions on Industrial Electronics 2022; 69: 10322-10332.
15. Zhai R., Zhou Z., Zhang W., Sang S., Li P. Control and navigation system for a fixed-wing unmanned aerial vehicle. AIP Advances 2014; 4: 031306.
16. Zhang J., Yan J. A novel control approach for flight-stability of fixed-wing UAV formation with wind field. IEEE Systems Journal 2021; 15: 2098-2108.