The invention discloses a high supersonic speed aircraft neural network composite learning control method based on a high gain observer and aims to solve a technical problem of poor practicality of ahigh supersonic speed aircraft control method in the prior art. The method is advantaged in that a strict feedback mode of an attitude subsystem is transformed to acquire an output feedback mode, a high gain observer is utilized to estimate unknown variables, and base is provided for subsequent controller design; system lumping uncertainty is considered, only one neural network is needed for approximation, the controller is simple to design, and engineering realization is facilitated; a system modeling error is introduced, composite new neural network learning rules are constructed, stable high supersonic speed aircraft neural control under uncertain situations is realized, and good practicality is realized.