一种适用于火星气动捕获的自适应预测制导算法

火星探测捕获制动需要的速度增量大，制动消耗燃料多，因此针对火星大气密度低、大气不确定性强等问题，提出一种基于解析及自适应预测校正结合的分段式气动捕获制导算法，实现无人钝头体飞行器由双曲线接近段轨道到目标停泊椭圆轨道的轨道转移.考虑到多约束条件，将制导算法分为高度数值预测校正 高度保持 入轨控制3个阶段，其中第三阶段使用基于一阶特征模型的全系自适应预测校正算法.该方法利用施加控制量的时间与最终半长轴改变量的关系形成动态输入变换，以抵消该系统一阶特征模型输入输出间巨大的动态增益.仿真结果表明，该算法即可满足一定的多约束条件，同时能够克服较强的初始条件不确定性和环境不确定性，具有较强的鲁棒性.

An Adaptive Prediction Guidance Algorithm for Mars Aerocapture

The velocity increment during Mars capture maneuvre is large, which results in large fuel consumption. Thus, focusing on Mars atmosphere characters such as low density and large environmental uncertainty, an aerocapture guidance algorithm is developed based on both analytical and numerical predictor corrector methods for blunt shape robotic aerocraft, which is designed to realize the orbit transfer from Mars approaching hyperbolic orbit to target elliptical orbit, without orbit insertion burn. Considering multiple boundary constraints, the guidance is divided into three phases which are numerical predictor corrector phase, height tracking phase, and targeting phase. The all coefficient adaptive guidance of the 3rd phase is built on first order characteristic model. To reduce the large time varying dynamic gain between input and output of the system’s characteristic model, the numerical relation between controlling time and the change of apoapsis range is introduced as the dynamic input variable. The simulation results show that this aerocapture guidance method is robust in various off nominal conditions, while meeting the requirements of some boundary constraints.