Control Surface Faults Neural Adaptive Compensation Control for Tailless Flying Wing Aircraft with Uncertainties

Abstract

A neural adaptive compensation tracking control scheme considering the prescribed tracking performance bound is proposed for a flying wing aircraft with control surface faults, actuator saturation and uncertainties of aerodynamic parameters. Second-order command filters are introduced to avoid the saturation of the actuators, prescribed performance bound strategy is designed to characterize the convergence rate and maximum overshoot of the tracking error, uncertainties of aerodynamic parameters are approximated by online RBF neural networks, and control allocation law is designed to reduce the coupling of the flight dynamics. The closed-loop control law is given based on adaptive backstepping compensation control scheme, and the stability of the closed-loop system is proved by Lyapunov based design. Simulation results are given to illustrate the effectiveness of the proposed neural adaptive compensation control scheme.