Fuzzy adaptive prescribed performance fault-tolerant control of hypersonic vehicles with multiple faults and input saturation

In this paper, a fuzzy adaptive prescribed performance attitude fault-tolerant control method for hypersonic vehicles is proposed to address full-state constraints, actuator and sensor faults, actuator saturation, and external disturbances. A fuzzy neural network-based fault estimation algorithm is proposed to estimate sensor faults. A fuzzy neural network extended state observer is designed to estimate system states and disturbances, thereby alleviating the effects of sensor faults and external uncertainties. To address the state constraint problem, a new prescribed performance control method with unknown initial error is designed to ensure that the tracking error remains within the preset range. Furthermore, a new anti-saturation compensation mechanism is designed to mitigate the effects of actuator saturation. The stability of the system is demonstrated through Lyapunov stability analysis. Simulation results show that the proposed control scheme is capable of achieving attitude tracking of hypersonic vehicles under multiple failure scenarios, thereby providing a reliable control strategy for the safety of hypersonic vehicles.