Maneuvering Decision-making Method of UAV Based on Approximate Dynamic Programming
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摘要: 针对空战机动决策时出现的“维数爆炸”问题，该文提出一种基于近似动态规划的群智能空战机动决策方法。首先建立无人机空气动力学模型和空战态势优势指标函数。其次，利用近似动态规划的思想，将空战过程按时间域划分为多个规划时域，在每个规划时域内，提出人工势场引导下的改进蚁狮优化算法快速逼近最优控制量，有效裁减搜索空间。通过与专家系统法进行仿真对比，表明所提方法解决高动态、实时性强的无人机机动决策问题的有效性和可行性。Abstract: To solve the problem of dimension disaster when solving air combat maneuvering decision-making by dynamic programming, a swarm intelligence maneuvering decision-making method based on the approximate dynamic programming is proposed. Firstly, the Unmanned Aerial Vehicle (UAV) dynamic model and advantage functions of situation are established. On this basis, air combat process is divided into several stages according to dynamic programming thought. In order to reduce the search space, an Artificial Potential Field (APF) Guiding Ant Lion Optimizer (ALO) approximate optimal control amount is adopted in each programming stage. Finally, by comparing expert system, the experiment result indicates that the high dynamic and real-time air combat maneuvering decision can be solved by the proposed method effectively.
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表 1 仿真实验初始参数
类型 x(m) y(m) z(m) v(m/s) $\theta $(°) $\psi $(°) 优势态势 无人机 5000 15000 5000 300 15 6 敌机 8000 10000 5000 270 10 20 劣势态势 无人机 6000 1000 6000 300 22 –15 敌机 2000 10000 6000 300 –9 12 
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