基于DDPG的高速飞行器预测校正制导律设计

Design of Predictor-Corrector Guidance Law for High-speed Vehicle based on DDPG

针对高速飞行器在再入滑翔过程中的多约束、强时变问题,本文结合深度确定性策略梯度算法(Deep Deterministic Policy Gradient, DDPG)的在线自主决策优势,根据威胁区信息,实时生成规避策略来进行动态禁飞区规避航迹规划。进一步为增强高速飞行器对环境不确定因素的抗干扰能力,在规避轨迹基础上选取航路特征点集合,采用预测校正在线制导方式,根据飞行任务需求和终端约束,实时校正高速飞行器飞行状态,最终实现高速飞行器精确制导。同时,为验证方法的有效性,开展了相应的数值仿真分析。结果表明,本文方法能够有效规避禁飞区,增强了对不确定因素的适应性,具有一定的工程应用价值。

Aiming at the multi-constraint and strongly time-varying problems of high-speed aircraft during re-entry gliding,this paper combines the online autonomous decision-making advantages of the Deep Deterministic Policy Gradient(DDPG)algorithm to generate avoidance strategies in real time based on threat zone information for dynamic no-fly zone avoidance trajectory planning.In order to further enhance the anti-interference ability of high-speed aircraft to environmental uncertainties,a set of route feature points is selected based on the avoidance trajectory,and a online predictor-corrector guidance method is used to correct the flight status of the high-speed aircraft in real time according to flight mission requirements and terminal constraints,and finally achieve precise guidance of high-speed aircraft.At the same time,in order to verify the effectiveness of the method,this paper carried out corresponding numerical simulation analysis.The results show that the method proposed in this paper can effectively avoid no-fly zones and enhance the adaptability to uncertain factors,and has certain engineering application value.