Disturbance observer–based neural adaptive fault-tolerant control for flexible air-breathing hypersonic vehicles with multiple model uncertainties

One of the critical problems for flexible vehicles is how to simultaneously address the multiple uncertainty compensation and flexible vibration suppression. This paper focuses on the smooth adaptive fault-tolerant control design problem of a two-layer framework for flexible air-breathing hypersonic vehicles subject to contingent actuator failures and multiple model uncertainties. The first layer provides a disturbance observer–based neural adaptive fault-tolerant controller overcoming actuator failures and multiple model uncertainties. The second layer relies on the tracking differentiator and filter combined with the controller seamlessly, generating smooth reference information, which is highly desirable for flexible vibration suppression. Then, the analysis by the Lyapunov theory strictly proves the uniform ultimately boundedness of all the control and filter state variables. Finally, the simulation results demonstrate the dominant tracking control performance of the proposed control method.