Intelligent Safety Flight Control With Variable Prescribed Performance

Amplitude constraints of Waverider Vehicles (WVs) will yield error fluctuations and further result in the singular problem of prescribed performance control (PPC), threatening the flight safety. It is the purpose of this study to propose a fuzzy-neural-approximation-based intelligent safety control method for WVs with actuator saturation. The saturation compensation is adopted by developing compensation systems to deal with the divergence of transformed error, which guarantees the realizability of prescribed performance. Moreover, performance functions are devised to construct a type of variable prescribed funnels which are actively readjusted based on actuator saturation. While the fragile problem associated with existing PPC is handled, and moreover quantitative prescribed performance indices are guaranteed for velocity tracking error and altitude tracking error of WVs. Besides, the addressed fuzzy-neural control does not require recursive design procedure of back-stepping and also avoids high computational burden. Finally, the superiority of design is validated via compared simulations.