基于大气预估的RLV再入预测制导研究

针对可重复使用飞行器(RLV)多约束再入制导特点,提出一种新的基于大气预估的再入制导方法. 针对大气模型的不确定性,通过参数辨识技术确定当前大气参数. 在此基础上,考虑可重复使用飞行器过载、动压和驻点热流等过程约束对倾侧角的限制,利用数值预测的方法实时预测RLV的落点确定制导偏差,形成倾侧角控制指令,完成再入轨道的在线设计. 仿真结果表明,该方法能够适应多种再入条件,有效减小各种不确定因素的影响,保证再入终端落点的精度要求. 

Reentry Predicted Guidance Algorithm for Reusable Launch Vehicles Based on Density Estimation

Follow the characteristics of multi-constraints reentry guidance for reusable launch vehicles (RLV), a new method of reentry guidance algorithm is put forward based on estimation of the density. With the technique of parameter-discriminated, the algorithm would find out the current condition of aerosphere. Further more, the algorithm could generate reasonable bank angle profiles with the consideration of path constraints such as heat rate flow, normal load and dynamic pressure. The predicted terminal location is then compared to normal condition, and the mismatch would be used to generate the magnitude of bank angle. Combining with lateral bank reversals, the on-line design of reentry guidance is completed finally. Simulation results demonstrate the effectiveness of the algorithm on achieving desired final conditions for different reentry initial conditions and atmospheric uncertainty.