Purpose In this paper, an innovative hybrid intelligent position control method for vertical take-off and landing (VTOL) tiltrotor unmanned aerial vehicle (UAV) is proposed. So the more accurate the reference position signals tracking, the proposed control system will be better. Design/methodology/approach In the proposed method, for the vertical flight mode, first the model reference adaptive controller (MRAC) operates and for the horizontal flight, the model predictive control (MPC) will operate. Since the linear model is used for both of these controllers and naturally has an error compared to the real nonlinear model, a neural network is used to compensate for them. So the main novelties of this paper are a new hybrid control design (MRAC & MPC) and a neural network-based compensator for tiltrotor UAV. Findings The proper performance of the proposed control method in the simulation results is clear. Also the results showed that the role of compensator is very important and necessary, especially in extreme speed wind conditions and uncertain parameters. Originality -Novel hybrid control method. -New method to use neural network as compensator in an UAV.
