An on-line re-entry guidance law employing model predictive algorithm for entry vehicle

In this paper, we propose a on-line re-entry guidance law employing model predictive algorithm. In the longitudinal profile, we use this method to predict flight capability from current condition by integrating to generate and track the reference drag acceleration profile on-line. In the lateral profile, we use the velocity azimuth angle error threshold to reduse heading error. At last, three degree of freedom simulation is implemented in various pneumatic deviation, the result demonstrates that our algorithm is computationally efficient and robust against uncertainties and disturbances.