Disturbance observer-based neural flight control for aircraft with switched time-varying distributed delays

In this article, the high angle of attack (AOA) maneuver control problem is studied under multiple disturbances and uncertainties. For the first time, the switched distributed delay is constructed to characterize the unsteady aerodynamics. Based on neural networks (NNs) and hyperbolic tangent function, the disturbance observer technique is extended to the nonstrict-feedback system control. To handle the switching problem, time-delay problem, and nonstrict-feedback problem caused by switched distributed delay terms, the Lyapunov-Krasovskii (LK) functional method and a variable separation method are cleverly combined. The proposed LK function can relax the constraints on time-varying delay. Finally, a disturbance observer-based neural finite-time prescribed performance flight control law is developed to improve the flight performance at high AOA, and its effectiveness has been verified through rigorous theoretical analysis and simulation experiments.

Automated summary

In this article, the high angle of attack maneuver control problem has been studied under multiple disturbances and uncertainties. A new approach based on neural networks and disturbance observer technique has been proposed to improve flight performance in high AOA conditions, which has been proven effective through rigorous theoretical analysis and simulation experiments.