Skip to main content
SpringerLink
Log in

Fuzzy Logic Based Approach to Design of Autonomous Landing System for Unmanned Aerial Vehicles

  • Published:
Journal of Intelligent & Robotic Systems Aims and scope Submit manuscript

Abstract

This paper is concerned with autonomous flight of UAVs and proposes a fuzzy logic based autonomous flight and landing system controller. Besides three fuzzy logic controllers which are developed for autonomous navigation for UAVs in a previous work as fuzzy logic based autonomous mission control blocks, three more fuzzy logic modules are developed under the main landing system for the control of the horizontal and the vertical positions of the aircraft against the runway under a TACAN (Tactical Air Navigation) approach. The performance of the fuzzy logic based controllers is evaluated using the standard configuration of MATLAB and the Aerosim Aeronautical Simulation Block Set which provides a complete set of tools for rapid development of 6 degree-of-freedom nonlinear generic manned/unmanned aerial vehicle models. Additionally, FlightGear Flight Simulator and GMS aircraft instruments are deployed in order to get visual outputs that aid the designer in evaluating the performance and the potential of the controllers. The simulated test flights on an Aerosonde indicate the capability of the approach in achieving the desired performance despite the simple design procedure.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Kurnaz, S., Cetin, O., Kaynak, O.: Fuzzy logic based approach to design flight control and navigation tasks for autonomous UAVs. J. Intell. Robot. Syst. 54, 229–244 (2009)

    Article  Google Scholar 

  2. Hodges, J.: Computer co-pilots. C4ISR Journal, September 2009, pp. 30–32 (2009)

  3. Fan, Y., Haiqing, S., Hong, W.: A vision-based algorithm for landing unmanned aerial vehicles. In: Computer Science and Software Engineering, 2008 International Conference, vol. 1, pp. 93–996, 12–14 Dec (2008)

  4. Koester, K.L., Vaillancourt, W.: TALONS 95 GHz radar sensor for autonomous landing guidance. IEEE Aerosp. Electron. Syst. Mag. 7(7), 40–44 (1992)

    Article  Google Scholar 

  5. Roy, E.F., Davison, J.W.: Autonomous landing guidance systems. IEEE Aerosp. Electron. Syst. Mag. 1(5), 10–15 (1986)

    Article  Google Scholar 

  6. Geske, J., MacDougal, M., Stahl, R., Wagener, J., Snyder, D.R.: Miniature laser rangefinders and laser altimeters. In: Avionics, Fiber-Optics and Photonics Technology Conference, 2008 IEEE, pp. 53–54, 30 Sept. 2008–2 Oct. (2008)

  7. Stengel, R.F.: Flight dynamics. Princeton University Press. ISBN 0-691-11407-2 (2004)

  8. Doitsidis, L., Valavanis, K.P., Tsourveloudis, N.C., Kontitsis, M.: A framework for fuzzy logic based UAV navigation and control. In: Proceedings of the International Conference on Robotics and Automation, vol. 4, pp. 4041–4046 (2004)

  9. Schumacher, C.J., Kumar, R.: Adaptive control of UAVs in close-coupled formation flight. Proc. Am. Control Conf. 2, 849–853 (2000)

    Google Scholar 

  10. Andrievsky, B, Fradkov, A.: Combined adaptive autopilot for an UAV flight control. In: Proceedings of the 2002 International Conference on Control Applications, vol. 1, pp. 290–291 (2002)

  11. Dufrene, W.R., Jr.: Application of artificial intelligence techniques in uninhabited aerial vehicle flight. In: The 22nd Digital Avionics Systems Conference, vo. 2, pp. 8.C.3–8.1–6 (2003)

  12. Li, Y., Sundararajan, N., Sratchandran, P.: Neuro-controller design for nonlinear fighter aircraft maneuver using fully tuned RBF networks. Automatica 37, 1293–1301 (2001)

    Article  MATH  Google Scholar 

  13. Marin, J.A., Radtke, R., Innis, D., Barr, D.R., Schultz, A.C.: Using a genetic algorithm to develop rules to guide unmanned aerial vehicles. Proc. IEEE Int. Conf. Syst. Man Cybern. 1, 1055–1060 (1999)

    Google Scholar 

  14. Ren, W., Beard, R.W.: CLF-based tracking control for UAV kinematic models with saturation constraints. In: Proceedings of the 42nd IEEE Conference on Decision and Control, vol. 4, pp. 3924–3929 (2003)

  15. Unmanned Dynamics: Aerosim aeronautical simulation block set version 1.2 user’s guide. http://www.u-dynamics.com/aerosim/default.htm. Last reached 12/27/2009

  16. FlightGear: Open-source flight simulator. www.flightgear.org. Last reached 12/27/2009

  17. Global Robotic Observation System: Definition of Aerosonde UAV specifications. http://www.aerosonde.com. Last reached 12/27/2009

  18. Cetin, O., Kaplan, M.Ç., Aydın, A.: Fuzzy Logic based autonomous UAV ground control station simulator design. In: Proceedings of 3rd National Defense Applications Modeling and Simulation Conference Poster Sessions, USMOS METU, pp. 163–169 (2009)

Download references

Author information

Authors and Affiliations

  1. Aeronautics and Space Technologies Institute, Turkish Air Force Academy, Yesilyurt, Istanbul, 34149, Turkey

    Omer Cetin & Sefer Kurnaz

  2. Department of Electrical and Electronic Engineering, Bogazici University, Bebek, 80815, Istanbul, Turkey

    Okyay Kaynak

Authors
  1. Omer Cetin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sefer Kurnaz
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Okyay Kaynak
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Omer Cetin.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Cetin, O., Kurnaz, S. & Kaynak, O. Fuzzy Logic Based Approach to Design of Autonomous Landing System for Unmanned Aerial Vehicles. J Intell Robot Syst 61, 239–250 (2011). https://doi.org/10.1007/s10846-010-9508-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10846-010-9508-6

Keywords

Search

Navigation