RLV再入轨迹机载快速优化

为了可重复使用飞行器再入轨迹机载快速优化的需求,开发一种再入轨迹快速优化算法。根据RLV再入三维轨迹的特点,引入了新的假设,对RLV再入轨迹状态方程进行简化处理,使优化迭代计算量大大减少,在此基础上,使用乘子法对再入终端约束进行处理,然后用共轭梯度法求解优化再入轨迹,最后以美国航天飞机为例计算再入最优轨迹。结果验证该算法在满足约束条件的情况下,具有很快的收敛速度,在不同初始再入条件和终端约束条件下,计算机时一般小于一分钟。该算法具有很好的工程应用前景。

Onboard Optimization Of Three-Dimensional Constrained Reentry Trajectory For RLV

Determining how to find the best controls of a re-entering reusable launch vehicle (RLV) so that it can safely reach Terminal Area Energy Management (TAEM) involved the solution of a two-point boundary value problem. This problem, which was considered to be difficult, was traditionally solved on the ground rather than onboard. The optimal controls were found regardless of computing time by the most of algorithms. But it was very necessary to find the optimal controls quickly for some flight tasks. Traditional trajectory optimization algorithms can not perform this fast optimization task. In this paper, according to the features of three-dimensional constrained reentry trajectory, a new hypothesis was introduced. The dynamics and kinematics equations of motion were divided into two sets and only one of those was involved in iterations of optimization algorithm, which improved the efficiency of optimization greatly. Then the methods of multipliers was used to deal with the terminal constraints. Later the Conjugate-Gradient Method was applied to evaluate the optimal reentry trajectory. Successful results show that this algorithm is able to generate a feasible reentry trajectory of about 2200 s flight time in 20-50 s on the desktop computer. The optimal trajectory can be used as the reference needed by guidance system.