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All Journal IAES International Journal of Robotics and Automation (IJRA)
Ali Moltajaei Farid
University of Sistan and Baluchestan, Zahedan, Iran.
Automotive Engineering Electrical & Electronics Engineering

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UAV Controller Based on Adaptive Neuro-Fuzzy Inference System and PID Ali Moltajaei Farid
IAES International Journal of Robotics and Automation (IJRA) Vol 2, No 2: June 2013
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (450.761 KB) | DOI: 10.11591/ijra.v2i2.pp73-82

Abstract

ANFIS is combining a neural network with a fuzzy system results in a hybrid neuro-fuzzy system, capable of reasoning and learning in an uncertain and imprecise environment. In this paper, an adaptive neuro-fuzzy inference system (ANFIS) is employed to control an unmanned aircraft vehicle (UAV).  First, autopilots structure is defined, and then ANFIS controller is applied, to control UAVs lateral position. The results of ANFIS and PID lateral controllers are compared, where it shows the two controllers have similar results. ANFIS controller is capable to adaptation in nonlinear conditions, while PID has to be tuned to preserves proper control in some conditions. The simulation results generated by Matlab using Aerosim Aeronautical Simulation Block Set, which provides a complete set of tools for development of six degree-of-freedom. Nonlinear Aerosonde unmanned aerial vehicle model with ANFIS controller is simulated to verify the capability of the system. Moreover, the results are validated by FlightGear flight simulator.
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