CAJ | 학술논문

针对传统预测制导方法中高精度制导与快速实时解算之间的矛盾，提出了一种基于最优制导模板的神经网络预测制导方法。该方法采用基于高置信度飞行器运动模型仿真计算预测弹道落点，利用优化理论进行迭代解算制导变量，以此为基础离线生成样本数据；通过选择合适的多结构模态神经网络，进行基于调度管理的神经网络训练，完成神经网络控制器的设计。针对CAV进行了算例设计，结果表明：该制导方法在线计算量少，制导解算速度快，制导精度高，综合性能远优于传统的预测制导方法。
침대전통예측제도방법중고정도제도여쾌속실시해산지간적모순，제출료일충기우최우제도모판적신경망락예측제도방법。해방법채용기우고치신도비행기운동모형방진계산예측탄도낙점，이용우화이론진행질대해산제도변량，이차위기출리선생성양본수거；통과선택합괄적다결구모태신경망락，진행기우조도관리적신경망락훈련，완성신경망락공제기적설계。침대CAV진행료산례설계，결과표명：해제도방법재선계산량소，제도해산속도쾌，제도정도고，종합성능원우우전통적예측제도방법。
In order to solve the contradiction between high guidance accuracy and fast real-time solving in traditional predictive guidance method, a neural network predictive guidance method is presented,based on the pattern of optimal guidance.The method predicts trajectory based on high believable simulation of kinematic aircraft model,and uses optimization theory to iterative solution of guide variable,so as to generate off-line sample data.By means of choosing multi-modal neural network,training neural network based on dispatching management,to complete the design of the neural network prediction guidance controller.CAV as an example to design,results show that:The method is less real time calculation,fast real-time solution and high guidance accuracy,of which the comprehensive performance is far better than the traditional predictive guidance method.