触地关机模式下的着陆器软着陆稳定性研究

以触地关机软着陆模式下的某型着陆器为研究对象，建立其软着陆过程的动力学仿真模型。基于仿真模型，结合优化方法与多岛遗传算法（MIGA）确定了着陆器的极恶劣地形工况参数，并利用径向基函数（RBF）神经网络建立了反映极恶劣工况下着陆器速度参数与稳定性指标值之间映射关系的代理模型。将着陆器速度参数做离散化处理得到样本点，利用神经网络模型计算了各样本点对应的软着陆稳定性指标值，基于计算结果给出了各项软着陆稳定性指标的云图和三维速度稳定性边界，并得到了综合各项稳定性指标的着陆器速度稳定性边界。分析结果可直观地确定保证着陆器安全着陆的速度取值范围，为着陆器速度的合理控制提供参考。 

Soft landing stability of lander in mode of shutdown at touchdown

A lander in the soft landing mode of shutdown at touchdown is taken as the research object, and the dynamic simulation model of its soft landing process is established. Based on the simulation model, the parameters of the worst landing conditions are obtained by combining optimization method and multi-island genetic algorithm (MIGA). The radial basis function (RBF) neural network is used to establish a surrogate model which reflects the mapping relationship between the lander's velocity parameter and the value of stability indicator. The sample points are obtained by discretizing the velocity parameters of the lander, and the soft landing stability performance of each sample point are calculated by using the neural network model. Based on the calculation results, the contour and the three-dimensional velocity stability boundary of each soft landing stability indicator are given, and then a comprehensive stability boundary of lander velocity is obtained. The analysis results can intuitively determine the range of velocity for safe landing, which provides reference for the rational control of lander velocity.