AEROSPACE SHANGHAI, Volume. 42, Issue 3, 117(2025)
Intelligent Cooperative Search for Multiple Flight Vehicles in Unknown Environment Based on Predictive Control
Figures & Tables(10)
Fig. 1. Cooperative search decision-making process of multiple flight vehicles
Fig. 2. Flight paths and coverage of the cooperative search with SSA
Fig. 3. Flight paths and coverage of the cooperative search with ISSA
Fig. 4. Flight paths and coverage of the cooperative search with GWO
Fig. 5. Flight paths and coverage of the cooperative search with strategy proposed in this paper
Fig. 6.
Fig. 7. Comparative analysis of the average number of targets searched per simulation under different methods
Table 1.
Intelligent search strategy based on the MPC and EESSA View tableView in ArticleTable 1.
Intelligent search strategy based on the MPC and EESSA 任务区域栅格化，目标存在概率图和信息确定度图初始化； For 决策次数=1∶40 For 获取当前时刻第 利用模型预测控制得到预测航迹 构建飞行器目标搜索任务规划优化问题模型； For t=1∶Tmax If 初始化麻雀种群； Else 更新生产者、追随者、警戒者麻雀数量； 利用贪心策略生成子代种群； 获取种群最优位置 End If End For 将 End For 飞行器间相互通信，交换航迹信息，更新搜索图； End For
Table 2.
Target information View tableView in ArticleTable 2.
Target information 目标序号 水平坐标 垂直坐标 1 15 15 2 15 25 3 30 25 4 7 10 5 12 30 6 20 13 7 32 32 8 30 23 9 38 15
Table 3.
Search results View tableView in ArticleTable 3.
Search results 搜索算法 搜索到的目标序号 搜索到的目标数 SSA 1，2，3，4，5，7，8 7 ISSA 1，2，3，4，5，6，7，8 8 GWO 1，2，3，4，5，6，7，8 8 本文策略 1，2，3，4，5，6，7，8，9 9
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Tao CHEN, Biao XU, Shuang LI, Xun SONG. Intelligent Cooperative Search for Multiple Flight Vehicles in Unknown Environment Based on Predictive Control[J]. AEROSPACE SHANGHAI, 2025, 42(3): 117
Paper Information
Category: Guidance, Navigation, Control and Electronics
Received: May. 29, 2024
Accepted: --
Published Online: Sep. 29, 2025
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