导弹与航天运载技术
導彈與航天運載技術
도탄여항천운재기술
MISSILES AND SPACE VEHICLES
2015年
3期
5-9
,共5页
再入滑翔%预测制导%BPNN%弹道优化%hp-自适应伪谱法
再入滑翔%預測製導%BPNN%彈道優化%hp-自適應偽譜法
재입활상%예측제도%BPNN%탄도우화%hp-자괄응위보법
Reentry glide%Predictor-corrector guidance%BPNN%Trajectory Optimization%hp-adaptive pseudospectral method
针对飞行器再入滑翔过程，提出一种跟踪优化弹道的BPNN（BP neural network）预测制导方法。首先着眼于多约束下弹道生成的快速性，利用hp-自适应伪谱法进行弹道优化；然后利用弹道样本数据训练BPNN，建立飞行状态参数与终端状态参数之间的非线性映射关系，实现对终端状态的预测；最后为制导律设计了双层线性反馈校正算法，从而完成预测制导关键环节。仿真算例该表明制导方法能够良好地满足再入飞行约束和终端约束，同时可以较好地实现对优化弹道的跟踪，并具有一定的鲁棒性和航程适应性。
針對飛行器再入滑翔過程，提齣一種跟蹤優化彈道的BPNN（BP neural network）預測製導方法。首先著眼于多約束下彈道生成的快速性，利用hp-自適應偽譜法進行彈道優化；然後利用彈道樣本數據訓練BPNN，建立飛行狀態參數與終耑狀態參數之間的非線性映射關繫，實現對終耑狀態的預測；最後為製導律設計瞭雙層線性反饋校正算法，從而完成預測製導關鍵環節。倣真算例該錶明製導方法能夠良好地滿足再入飛行約束和終耑約束，同時可以較好地實現對優化彈道的跟蹤，併具有一定的魯棒性和航程適應性。
침대비행기재입활상과정，제출일충근종우화탄도적BPNN（BP neural network）예측제도방법。수선착안우다약속하탄도생성적쾌속성，이용hp-자괄응위보법진행탄도우화；연후이용탄도양본수거훈련BPNN，건립비행상태삼수여종단상태삼수지간적비선성영사관계，실현대종단상태적예측；최후위제도률설계료쌍층선성반궤교정산법，종이완성예측제도관건배절。방진산례해표명제도방법능구량호지만족재입비행약속화종단약속，동시가이교호지실현대우화탄도적근종，병구유일정적로봉성화항정괄응성。
A BPNN predictor-corrector guidance method that tracks the optimized trajectory of hypersonic reentry glide process is presented. First, based on the trajectory generation rapidity under multiple constraints, the hp-adaptive pseudospectral method is used to optimize the trajectory. Then a BPNN (BP neural network) is trained with parameter data of optimized trajectory to simulate the nonlinear mapping relationship between the current flight states and terminal states. Hence, the guidance is achieved by nullifying the terminal errors. Simulation examples show that the guidance method based on trajectory optimization and neural network can satisfy both reentry flight and terminal constraints and have good robustness and validity.
