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In this paper, we present a neural adaptive backstepping flight controller for a ducted fan UAV whose dynamics is characterized by uncertainties and highly coupled nonlinearities. The proposed neural adaptive back-stepping controller can handle unknown nonlinearities, unmodeled dynamics and external wind disturbances. A single layer radial basis function network is used to approximate the virtual control law derived using back stepping approach, which provides necessary stability and tracking performances. The neural controller parameters are adapted online using Lyapunov based update laws. The proposed controller is evaluated using nonlinear desktop simulation model of a typical ducted fan UAV performing bop-up maneuver. Three neural adaptive controllers are implemented to handle attitude command altitude hold system, one in each body axis. A separate neural controller is implemented to track the height command for autonomous takeoff and landing. The results indicate that the proposed controller can stabilize the ducted fan UAV and provide necessary tracking performance.

This paper presents a neural adaptive flight controller for ducted fan UAVs which are capable of vertical takeoff and landing(VTOL). These ducted fan propulsion systems pose great challenges in aerodynamics and control and we propose a backstepping neural adaptive control law to track its nonlinear dynamics. This controller can handle unmodeled dynamics and external disturbances as well, providing stability to the vehicle. A single layer radial basis neural network is used to approximate the unmodeled dynamics and vehicle stability is guaranteed through Lyapunov synthesis. For simulation study six degree of freedom model (6-DOF) is implemented in MATLAB along with the proposed control approach. The performance of the controller is evaluated using nonlinear bop-up maneuver and the necessary stability and tracking performance of the UAV have been investigated.Index Terms-Ducted fan, Adaptive Back stepping, Radial basis function neural networks, Lyapunov stability.

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