Robust Adaptive Trajectory Tracking Control for Fixed-Wing Unmanned Aerial Vehicles

Accurate trajectory tracking is crucial for fixed-wing unmanned aerial vehicles (UAVs) in executing diverse missions. However, the inherent strong nonlinearities, parametric uncertainties, and external disturbances in the UAV model present significant challenges for controller design. To address these challenges, this paper proposes a robust adaptive control strategy based on the backstepping technique. The proposed strategy effectively addresses a class of uncertainties with norm bounds that are unknown and state-dependent. An adaptive law is constructed to estimate the unknown parameters online, thereby enabling compensation for the effects of these uncertainties. Furthermore, to mitigate chattering, the controller is modified to generate smooth control inputs, ensuring that the steady-state tracking error is ultimately bounded and converges to an arbitrarily small neighborhood of zero. Simulation results demonstrate that, under realistic flight control sampling frequencies, the proposed controller achieves accurate trajectory tracking and eliminates the chattering phenomenon.