基于深度学习的时间角度控制制导律  

Time and angle control guidance law based on deep learning

作　　者：刘子超 王江[1,2] 何绍溟 LIU Zichao;WANG Jiang;HE Shaoming(School of Aerospace Engineering,Beijing Institute of Technology,Beijing 100081,China;China-UAE Belt and Road Joint Laboratory on Intelligent Unmanned Systems,Beijing Institute of Technology,Beijing 100081,China;Yangtze Delta Region Academy of Beijing Institute of Technology(Jiaxing),Jiaxing 314019,China)

机构地区：[1]北京理工大学宇航学院,北京100081 [2]北京理工大学中国-阿联酋智能无人系统“一带一路”联合实验室,北京100081 [3]北京理工大学长三角研究院(嘉兴),浙江嘉兴314019

出　　处：《系统工程与电子技术》2023年第11期3579-3587,共9页Systems Engineering and Electronics

基　　金：国家自然科学基金(61827901)资助课题。

摘　　要：针对考虑导弹气动力的时间角度控制制导问题,设计了一种基于深度学习的时间角度控制制导律;设计预测模块对考虑气动力的飞行器剩余飞行时间进行预测,预测模块引入前馈环节融合深度学习方法与理论模型,使用理论模型估计剩余飞行时间,使用深度神经网络估计理论模型的预测误差,提高剩余飞行时间预测精度;将精确剩余飞行时间引入时间角度控制制导律,使飞行时间误差收敛至零附近,最终实现飞行时间和攻击角度的共同控制。通过仿真试验验证了所设计的制导方法能够实现时间角度控制,相对于基于常值速度假设提出的制导律具有更好的制导性能。A deep learning-based impact time and angle control guidance algorithm is proposed to solve the impact time and angle control problem of missile guidance under aerodynamic force.A predictor module is designed for estimating the exact impact time under optimal impact angle guidance law with realistic aerodynamic characteristics,and a feedforward loop for fusing the theoretical model and deep learning method is presented.An approximate time-to-go is predicted by the theoretical model and the prediction error is estimated by deep neural networks,so that the accuracy of prediction is improved.The impact time error could converge to zero after introducing the exact impact time into guidance law,then the joint control of the impact time and the terminal impact angle is achieved.The simulation results show that the designed guidance algorithm can realize the impact time and angle control more accurately compared with that based on a constant velocity assumption.

关 键 词：导弹制导 飞行时间控制 攻击角度控制 深度学习 

分 类 号：TJ765.3[兵器科学与技术—武器系统与运用工程]