Flight Control of Waverider Vehicles with Fragility-avoidance Prescribed Performance

This article proposes a prescribed performance control (PPC) methodology called fragility-avoidance PPC for waverider vehicles (WVs) with sudden disturbances based on fuzzy neural approximation. We raise the fragile problem associated with the existing PPC, and to remedy this defect, we construct a flexible prescribed funnel that is able to sense the error fluctuation caused by sudden disturbances and, moreover, tackle the fragile problem by automatically adjusting prescribed boundaries. Then, a simplified fuzzy neural approximation framework is presented to reject the unknown nonaffine dynamics of WVs while avoiding the algebraic loop problem. The stability of the closed-loop system is proved via the Lyapunov method, and finally, the effectiveness and superiority of the addressed method are verified by compared simulations.