LAUSR

A novel adaptive critic design (ACD) guaranteeing presented performance is addressed for hypersonic vehicles (HVs). In the previous studies, most ACDs focus on affine systems while ACD-based nonaffine tracking control is rare. In this paper, we propose a direct nonaffine tracking control method for HVs utilizing ACD. Within the framework of ACD, fuzzy wavelet neural networks (FWNNs) are applied to build action networks and critic networks. Via an analytically invertible model approach, novel direct nonaffine controllers are developed, based on which together with FWNN approximations, action networks are devised to yield the main control laws. Furthermore, FWNNs are also used to develop critic networks, strengthening commend tracking performance provided by action networks. To achieve predefined performance consisting of transient performance and steady-state performance, prescribed performance control is employed to impose behavioral limitations on velocity and altitude tracking errors. Finally, numerical simulations are implemented to test the design.