Summary: Nearspace morphing vehicles possess telescopic winglets. Aircraft stability may be affected by parameter perturbations, which are caused by the large-range hop to the state and the control volume of the aircraft during the stretching and withdrawal of the winglet. An adaptive sliding mode control method that combines fast double-power reaching law sliding mode with a neural network is proposed in this paper. A sliding mode controller is designed on the basis of the fast double-power reaching law. The neural network is used to model complex nonlinear relationships to obtain the reaching law of the sliding mode throughout the entirety of the stretching and withdrawal processes of the winglet. The proposed method is compared with the traditional sliding mode control method. The simulation results showed that the proposed method has an excellent control effect.