摘要
建立了多无人机协同任务规划模型,从时间和空间上分析了影响任务分配的关键技术指标,以考虑雷达站下无人机的飞行总航程、攻击目标收益、完成任务时间和执行任务时的威胁代价为子目标函数,建立了多机任务分配模型。将多目标规划问题转化为单目标规划,运用主客观赋权法计算各指标的权重。提出了改进的遗传算法用于求解模型,提高了任务规划效率。考虑两种载荷的限制,对规划路线进行优化。仿真结果表明:提出的模型和算法能有效地解决多机协同任务规划问题。
A multi-UAV cooperative mission planning model was established.The key technical indicators affecting task allocations were analyzed,and the sub-objective function takes into account the total flight range,target gain,mission completion time and threat cost of UAV under radar station as its sub-objective function.A multi-machine task allocation model was established.The multi-objective programming problem was transformed into single-objective programming,and the weight of each index was calculated by subjective and objective weighting method.An improved genetic algorithm was proposed to solve the model,which improves the efficiency of task planning.Considering the limitation of two kinds of loads,the planning route was optimized.The simulation results show that the proposed model and algorithm can effectively solve the problem of multi-machine cooperative task planning.
作者
张哲
吴剑
何诚
穆忠伟
ZHANG Zhe;WU Jian;HE Cheng;MU Zhongwei(Nanchang Hangkong University,Nanchang 330063,China;No.650 Research Institute of Hongdu Aviation Industry Group,Nanchang 330024,China)
出处
《兵器装备工程学报》
CAS
北大核心
2020年第2期123-128,共6页
Journal of Ordnance Equipment Engineering
基金
航空科学基金项目(2016ZC56003)
南昌航空大学研究生创新专项资金项目(YC2019026).
关键词
无人机
协同任务规划
多目标
权重
改进遗传算法
UAV
cooperative task planning
multiple target
weight
improved genetic algorithm
作者简介
张哲(1995—),男,硕士研究生,主要从事无人机任务分配及航迹规划研究;通讯作者:吴剑(1975—),男,博士,副教授,主要从事先进控制理论研究,E-mail:78313993@qq.com。
