Adaptive Neuro-Fuzzy Inference System Based Autonomous Flight Control of Unmanned Air Vehicles

  • Authors:

  • Sefer Kurnaz;Okyay Kaynak;Ekrem Konakoğlu

  • Affiliations:

  • Aeronautics and Space Technologies Institute, Air Force Academy, Yesilkoy, Istanbul, Turkey;Aeronautics and Space Technologies Institute, Air Force Academy, Yesilkoy, Istanbul, Turkey and BogaziciUniversity, Bebek, 34342 Istanbul, Turkey;Aeronautics and Space Technologies Institute, Air Force Academy, Yesilkoy, Istanbul, Turkey

  • Venue:
  • ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks
  • Year:
  • 2007

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Abstract

This paper proposes ANFIS logic based autonomous flight controller for UAVs (unmanned aerial vehicles). Three fuzzy logic modules are developed for the control of the altitude, the speed, and the roll angle, through which the altitude and the latitude-longitude of the air vehicle is controlled. The implementation framework utilizes MATLAB's standard configuration and the Aerosim Aeronautical Simulation Block Set which provides a complete set of tools for rapid development of detailed 6 degree-of-freedom nonlinear generic manned/unmanned aerial vehicle models. The Aerosonde UAV model is used in the simulations in order to demonstrate the performance and the potential of the controllers. Additionally, Microsoft Flight Simulator and FlightGear Flight Simulator are deployed in order to get visual outputs that aid the designer in the evaluation of the controllers. Despite the simple design procedure, the simulated test flights indicate the capability of the approach in achieving the desired performance.