Physics

Aerospace engineering

Nonlinear system

Hypersonic flight

Lyapunov redesign

Evolutionary biology

Biology

Aerodynamics

Hypersonic speed

Engineering

Function (biology)

Actuator

Artificial intelligence

Control (management)

Constraint (computer-aided design)

Computer science

Angle of attack

Quantum mechanics

Control theory (sociology)

Lyapunov function

Mechanical engineering

IEEE Transactions on Cybernetics

This paper investigates a fault-tolerant control of the hypersonic flight vehicle using back-stepping and composite learning. With consideration of angle of attack (AOA) constraint caused by scramjet, the control laws are designed based on barrier Lyapunov function. To deal with the unknown actuator faults, a robust adaptive allocation law is proposed to provide the compensation. Meanwhile, to obtain good system uncertainty approximation, the composite learning is proposed for the update of neural weights by constructing the serial–parallel estimation model to obtain the prediction error which can dynamically indicate how the intelligent approximation is working. Simulation results show that the controller obtains good system tracking performance in the presence of AOA constraint and actuator faults.

Barrier Lyapunov Function Based Learning Control of Hypersonic Flight Vehicle With AOA Constraint and Actuator Faults