Computational Experimental Test on PID Controlled Fixed Wing Aircraft Systems
Article Information
Abstract
This paper focuses on the implementation of a control framework for a fixed wing aircraft system and the simulation demonstrations. The aim is to develop several Proportional Integral Derivative (PID) controllers to stabilise the altitude and attitude in a 2D environment by regulating the engine power, the pitch angle, and height in flight operation. In technique, a dynamic mathematical model is established by considering the degrees of freedom and the dynamics of motion of a fixed wing aircraft, which provide a foundation for design and simulation. A simplified aircraft dynamic model is tailored for testing the formed control systems, which can be flexibly modified with different aircraft configurations, for a showcase illustration a calculation of the moment of inertia is included. Further, several flight settings such as height differences and velocities are proposed and a feasible implementation of the PID controllers is introduced for adjusting the control variables, and further a switching mode with two controllers for the height with different speeds are simulated to select the height linked controllers.
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References
- Raymer, D. (2012). Aircraft design: a conceptual approach. American Institute of Aeronautics and Astronautics, Inc..
[CrossRef] [Google Scholar] - Bulka, E., & Nahon, M. (2019). Automatic control for aerobatic maneuvering of agile fixed-wing UAVs. Journal of Intelligent & Robotic Systems, 93(1), 85-100.
[CrossRef] [Google Scholar] - Lunze, J. (2010). Regelungstechnik 1: Systemtheoretische grundlagen, analyse und entwurf einschleifiger regelungen. Berlin, Heidelberg: Springer Berlin Heidelberg.
[CrossRef] [Google Scholar] - Faradonbeh, M. K. S., Tewari, A., & Michailidis, G. (2020). On adaptive linear–quadratic regulators. Automatica, 117, 108982.
[CrossRef] [Google Scholar] - Aliyu, M. D. S. (2011). Nonlinear H$\infty$-control, Hamiltonian systems and Hamilton-Jacobi equations. CRC.
[CrossRef] [Google Scholar] - Kouvaritakis, B., & Cannon, M. (2016). Model predictive control. Switzerland: Springer International Publishing, 38(13-56), 7.
[CrossRef] [Google Scholar] - Zhao, S., Wang, X., Zhang, D., & Shen, L. (2017). Model-free fuzzy adaptive control of the heading angle of fixed-wing unmanned aerial vehicles. Journal of Aerospace Engineering, 30(4), 04017019.
[CrossRef] [Google Scholar] - Lin, F. (2007). Robust control design: an optimal control approach. John Wiley & Sons.
[Google Scholar] - Stevens, B. L., Lewis, F. L., & Johnson, E. N. (2015). Aircraft control and simulation: dynamics, controls design, and autonomous systems. John Wiley & Sons.
[Google Scholar] - Marqués, P., & Da Ronch, A. Advanced UAV Aerodynamics, Flight Stability and Control.
[CrossRef] [Google Scholar] - Nicolai, L. M., & Carichner, G. E. (2010). Fundamentals of aircraft and airship design: Volume I–aircraft design. American Institute of Aeronautics and Astronautics, Inc..
[CrossRef] [Google Scholar] - Liu, H. H., & Zhu, B. (2018). Formation control of multiple autonomous vehicle systems. John Wiley & Sons.
[CrossRef] [Google Scholar] - Anderson, J. (2023). ISE Ebook Online Access for Fundamentals of Aerodynamics. McGraw-Hill US Higher Ed ISE.
[Google Scholar] - Bohl, W., & Elmendorf, W. (1980). Technische Strömungslehre: Stoffeigenschaften von Flüssigkeiten und Gasen, Hydrostatik, Aerostatik, inkompressible Strömungen, kompressible Strömungen, Strömungsmesstechnik. Vogel.
[Google Scholar] - Ntantis, E. L., & Xezonakis, V. (2025). Aerodynamic design optimization of a NACA 0012 airfoil: An introductory adjoint discrete tool for educational purposes. International Journal of Mechanical Engineering Education, 53(3), 611-630.
[CrossRef] [Google Scholar] - Center of pressure. (n.d.). NASA Glenn Research Center. Retrieved from https://www.grc.nasa.gov/www/k-12/VirtualAero/BottleRocket/airplane/cp.html
[Google Scholar] - Extra 300 LX. (n.d.). World of The Flying Bulls. Retrieved from https://www.flyingbulls.at/en/fleet/extra-300-lx
[Google Scholar] - Kassera, W. (2017). Motorflug kompakt. Das Grundwissen zur Privatpilotenlizenz. Stuttgart.
[Google Scholar] - Bender, B., & Göhlich, D. (2020). Dubbel Taschenbuch Für Den Maschinenbau 2. Springer Berlin/Heidelberg.
[CrossRef] [Google Scholar] - Buchholz, J. (2016). Regelungstechnik und Flugregler. Ergänzte Auflage.
[Google Scholar] - Borase, R. P., Maghade, D. K., Sondkar, S. Y., & Pawar, S. N. (2021). A review of PID control, tuning methods and applications. International Journal of Dynamics and Control, 9(2), 818-827.
[CrossRef] [Google Scholar] - Mao, Q., Xu, Y., Chen, J., Chen, J., & Georgiou, T. T. (2024). Maximization of gain/phase margins by PID control. IEEE Transactions on Automatic Control, 70(1), 34-49.
[CrossRef] [Google Scholar] - Papula, L. (2009). Mathematik für Ingenieure und Naturwissenschaftler, Band 1+ 2. Vieweg+ Teubner Verlag, Wiesbaden.
[CrossRef] [Google Scholar]
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Cite This Article
TY - JOUR AU - Horstkötter, Eileen AU - Zhu, Quanmin PY - 2025 DA - 2025/05/18 TI - Computational Experimental Test on PID Controlled Fixed Wing Aircraft Systems JO - ICCK Transactions on Sensing, Communication, and Control T2 - ICCK Transactions on Sensing, Communication, and Control JF - ICCK Transactions on Sensing, Communication, and Control VL - 2 IS - 2 SP - 95 EP - 105 DO - 10.62762/TSCC.2025.731885 UR - https://www.icck.org/article/abs/TSCC.2025.731885 KW - aircraft dynamic modelling KW - control systems KW - PID KW - simulation KW - Matlab/Simulink AB - This paper focuses on the implementation of a control framework for a fixed wing aircraft system and the simulation demonstrations. The aim is to develop several Proportional Integral Derivative (PID) controllers to stabilise the altitude and attitude in a 2D environment by regulating the engine power, the pitch angle, and height in flight operation. In technique, a dynamic mathematical model is established by considering the degrees of freedom and the dynamics of motion of a fixed wing aircraft, which provide a foundation for design and simulation. A simplified aircraft dynamic model is tailored for testing the formed control systems, which can be flexibly modified with different aircraft configurations, for a showcase illustration a calculation of the moment of inertia is included. Further, several flight settings such as height differences and velocities are proposed and a feasible implementation of the PID controllers is introduced for adjusting the control variables, and further a switching mode with two controllers for the height with different speeds are simulated to select the height linked controllers. SN - 3068-9287 PB - Institute of Central Computation and Knowledge LA - English ER -
@article{Horstktter2025Computatio,
author = {Eileen Horstkötter and Quanmin Zhu},
title = {Computational Experimental Test on PID Controlled Fixed Wing Aircraft Systems},
journal = {ICCK Transactions on Sensing, Communication, and Control},
year = {2025},
volume = {2},
number = {2},
pages = {95-105},
doi = {10.62762/TSCC.2025.731885},
url = {https://www.icck.org/article/abs/TSCC.2025.731885},
abstract = {This paper focuses on the implementation of a control framework for a fixed wing aircraft system and the simulation demonstrations. The aim is to develop several Proportional Integral Derivative (PID) controllers to stabilise the altitude and attitude in a 2D environment by regulating the engine power, the pitch angle, and height in flight operation. In technique, a dynamic mathematical model is established by considering the degrees of freedom and the dynamics of motion of a fixed wing aircraft, which provide a foundation for design and simulation. A simplified aircraft dynamic model is tailored for testing the formed control systems, which can be flexibly modified with different aircraft configurations, for a showcase illustration a calculation of the moment of inertia is included. Further, several flight settings such as height differences and velocities are proposed and a feasible implementation of the PID controllers is introduced for adjusting the control variables, and further a switching mode with two controllers for the height with different speeds are simulated to select the height linked controllers.},
keywords = {aircraft dynamic modelling, control systems, PID, simulation, Matlab/Simulink},
issn = {3068-9287},
publisher = {Institute of Central Computation and Knowledge}
}
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