Aiming at the development of more affordable, convenient and reliable access to space, aerospace vehicle (ASV) has received sustained attention during the last few decades. Due to the wide flight envelope from suborbital to atmosphere, reaction control system (RCS) is usually used to assist aerodynamic surfaces to complete the attitude control of the reentry ASV. To solve the problem of blended control allocation, this paper puts forward some relevant solutions. First, the model predictive controller (MPC) is designed, in which, a prediction model and a rolling optimizer are added. Then, on the basis of traditional optimization allocation algorithm, this paper takes the response speed of actuators into account in the optimization index, and establishes a dynamic allocation algorithm based on quadratic programming. Finally, the comparison simulations between traditional controller and MPC, traditional optimization algorithm and dynamic allocation algorithm are carried out respectively. The results demonstrate that MPC method provides faster response speed and better tracking performance, and the dynamic allocation algorithm reduces the energy consumption of RCS while improving the control accuracy.