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首页> 美国政府科技报告 >Simulation of a Swarm of Unmanned Combat Air Vehicles (UCAVS).
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Simulation of a Swarm of Unmanned Combat Air Vehicles (UCAVS).

机译：一群无人作战飞行器（UCaVs）的仿真研究。

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This research focuses on the control of the collective performance of a swarm of UCAVs. One control command string controls the motion of all UCAVs in a mission. There is no explicit coordination among diem. If the control command string is properly chosen, the motion of the swarm of UCAVs will perform well collectively. Genetic Algorithms (GA) are used in this research to find suitable control command strings. It is an effective method to get a very good solution if the mathematical optimum is not necessary. The objective is for UCAVs to maximize surveillance coverage in 20 time steps. The final fitness value is the average of the coverage percentiles of five 20-time-step results. Using GA, the best control command string found to control 10 UCAVs has the fitness value 0. 9603. This is an average of 96.03% of coverage, a very good result. Parametric and robustness analyses show that control may not be very robust. Monte Carlo simulation in conjunction with Genetic Algorithm is used to evolve robust control when wind-gust disturbance exists. The results of different approaches are compared.

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