Fault-Tolerant Attitude Control of Hypersonic Flight Vehicles Based on Extended Adaptive Iterative Learning

This paper proposes an attitude fault-tolerant control scheme for hypersonic flight vehicles based on extended adaptive iterative learning. Firstly, the integral of tracking error is introduced as an extended state variable. Then, a controller based on iterative learning is designed to obtain the optimal feedback control law without faults. Additionally, for multiplicative faults in actuators, a model reference adaptive unit is expansively added to improve the system’s robustness under faulty conditions by tracking a reference model. Finally, the stability of the two control modules is proven, and the method is validated in a Matlab simulation environment to achieve good attitude control performance in both fault-free and faulty scenarios.