Computational Experimental Test on PID Controlled Fixed Wing Aircraft Systems
Research Article  ·  Published: 18 May 2025
Issue cover
ICCK Transactions on Sensing, Communication, and Control
Volume 2, Issue 2, 2025: 95-105
Research Article Free to Read

Computational Experimental Test on PID Controlled Fixed Wing Aircraft Systems

1 School of Engineering, University of the West of England, Bristol BS16 1QY, United Kingdom
* Corresponding Author: Quanmin Zhu, [email protected]
Volume 2, Issue 2

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.

Graphical Abstract

Computational Experimental Test on PID Controlled Fixed Wing Aircraft Systems

Keywords

aircraft dynamic modelling control systems PID simulation Matlab/Simulink

Data Availability Statement

Data will be made available on request.

Funding

This work was supported without any funding.

Conflicts of Interest

The authors declare no conflicts of interest.

Ethical Approval and Consent to Participate

Not applicable.

References

  1. Raymer, D. (2012). Aircraft design: a conceptual approach. American Institute of Aeronautics and Astronautics, Inc..
    [CrossRef] [Google Scholar]
  2. 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]
  3. Lunze, J. (2010). Regelungstechnik 1: Systemtheoretische grundlagen, analyse und entwurf einschleifiger regelungen. Berlin, Heidelberg: Springer Berlin Heidelberg.
    [CrossRef] [Google Scholar]
  4. Faradonbeh, M. K. S., Tewari, A., & Michailidis, G. (2020). On adaptive linear–quadratic regulators. Automatica, 117, 108982.
    [CrossRef] [Google Scholar]
  5. Aliyu, M. D. S. (2011). Nonlinear H$\infty$-control, Hamiltonian systems and Hamilton-Jacobi equations. CRC.
    [CrossRef] [Google Scholar]
  6. Kouvaritakis, B., & Cannon, M. (2016). Model predictive control. Switzerland: Springer International Publishing, 38(13-56), 7.
    [CrossRef] [Google Scholar]
  7. 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]
  8. Lin, F. (2007). Robust control design: an optimal control approach. John Wiley & Sons.
    [Google Scholar]
  9. 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]
  10. Marqués, P., & Da Ronch, A. Advanced UAV Aerodynamics, Flight Stability and Control.
    [CrossRef] [Google Scholar]
  11. 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]
  12. Liu, H. H., & Zhu, B. (2018). Formation control of multiple autonomous vehicle systems. John Wiley & Sons.
    [CrossRef] [Google Scholar]
  13. Anderson, J. (2023). ISE Ebook Online Access for Fundamentals of Aerodynamics. McGraw-Hill US Higher Ed ISE.
    [Google Scholar]
  14. Bohl, W., & Elmendorf, W. (1980). Technische Strömungslehre: Stoffeigenschaften von Flüssigkeiten und Gasen, Hydrostatik, Aerostatik, inkompressible Strömungen, kompressible Strömungen, Strömungsmesstechnik. Vogel.
    [Google Scholar]
  15. 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]
  16. 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]
  17. Extra 300 LX. (n.d.). World of The Flying Bulls. Retrieved from https://www.flyingbulls.at/en/fleet/extra-300-lx
    [Google Scholar]
  18. Kassera, W. (2017). Motorflug kompakt. Das Grundwissen zur Privatpilotenlizenz. Stuttgart.
    [Google Scholar]
  19. Bender, B., & Göhlich, D. (2020). Dubbel Taschenbuch Für Den Maschinenbau 2. Springer Berlin/Heidelberg.
    [CrossRef] [Google Scholar]
  20. Buchholz, J. (2016). Regelungstechnik und Flugregler. Ergänzte Auflage.
    [Google Scholar]
  21. 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]
  22. 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]
  23. Papula, L. (2009). Mathematik für Ingenieure und Naturwissenschaftler, Band 1+ 2. Vieweg+ Teubner Verlag, Wiesbaden.
    [CrossRef] [Google Scholar]

Cited By (2)

  1. Mariana Akemi Ikegawa Bernabé, Rafael González Perea, Juan Antonio Rodríguez Díaz, Jorge García Morillo. Transformer-based artificial intelligence for forecasting energy demand in irrigation districts. Computers and Electronics in Agriculture, 2026 , 246 .
    [CrossRef]
  2. Venkateswarlu G, E. Sampad, Umakanta Nanda, J. Bhaskara Rao, C. V. M. Chaturvedi, Nalini Bodasingi. Numerical Modeling of High-Efficiency Lead-Free $$\hbox {Cs}_{{2}} \hbox {PtI}_{{6}}$$/$$\hbox {MgHfS}_{{3}}$$ Tandem Perovskite Solar Cells Using SCAPS-1D. Journal of Electronic Materials, 2026 , 55 (1).
    [CrossRef]
* Citation data provided by Crossref Cited-by.

Cite This Article

APA Style
Horstkötter, E., & Zhu, Q. (2025). Computational Experimental Test on PID Controlled Fixed Wing Aircraft Systems. ICCK Transactions on Sensing, Communication, and Control, 2(2), 95–105. https://doi.org/10.62762/TSCC.2025.731885
Export Citation
RIS Format
Compatible with EndNote, Zotero, Mendeley, and other reference managers
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  - 
BibTeX Format
Compatible with LaTeX, BibTeX, and other reference managers
@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}
}

Article Metrics

Citations
Views
1235
PDF Downloads
770

Publisher's Note

ICCK stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and Permissions

Institute of Central Computation and Knowledge (ICCK) or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
ICCK Transactions on Sensing, Communication, and Control
ICCK Transactions on Sensing, Communication, and Control
ISSN: 3068-9287 (Online) | ISSN: 3068-9279 (Print)
Portico
Preserved at
Portico