In this paper, we proposed a neural-network-based adaptive controller to adapt against unknown, possibly time varying, external disturbances for a quadrotor UAV. The proposed algorithm can estimate uncertain forces, which occurs when flying in narrow areas, near walls and/or other surfaces, so that the controller can maintain satisfactory position tracking performance despite these disturbances. A proof for stability with the proposed algorithm is provided. Experimental results show that, with the proposed NN based adaptation algorithm, position tracking performance of quadrotor UAV shows satisfactory improvement in presence of external disturbances.
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