An Adaptive Nonlinear Control Approach for Quadrotor Uav Trajectory Tracking

Quadrotor unmanned aerial vehicles are nonlinear and underactuated systems whose control performance is strongly affected by model uncertainties and external disturbances. This paper presents an adaptive nonlinear control approach for quadrotor UAV trajectory tracking. The proposed strategy is developed from an adaptive fuzzy control framework for a general second-order nonlinear system, in which the control signal is generated through a Sugeno-type fuzzy structure and the controller parameters are updated online according to adaptive laws derived from the Lyapunov stability criterion. The resulting control architecture is then extended to the position and attitude subsystems of the quadrotor through six control channels with corresponding adaptive parameter update laws. Simulation results show that the quadrotor can follow the prescribed trajectory with stable position and attitude responses, while the tracking errors remain bounded and decrease toward a small neighborhood of zero. The results indicate that the proposed adaptive nonlinear control structure provides good adaptability and satisfactory tracking performance under the considered operating conditions. Therefore, the proposed approach is a feasible solution for quadrotor UAV control in the presence of uncertainties and disturbances.