Adaptive Neural Altitude Control and Attitude Stabilization of a Hexacopter with Uncertain Dynamics

Unmanned Aerial Vehicles (UAVs) are recently attracting significant research attention due to their potential applications in many fields. Hexacopter UAV offers higher payloads handling and faults tolerance than a quadcopter but its control is a demanding task. In this paper, an adaptive Neural Networks (NN) controller is proposed for altitude tracking and attitude stabilization of a hexacopter UAV with uncertain dynamics. The controller design, simulation and robustness against gust disturbances are discussed. Also, the controller performance is compared with a standard Filtered-Proportional-Derivative-Integrator (FPID) controller for different control scenarios.