不确定环境下无人机多目标任务分配问题研究

Research on Multi-target Assignment of UAV under Uncertain Environment

基于不确定理论,研究了不确定环境下无人机多目标任务分配问题。首先,引入不确定变量来描述任务分配规划中存在的不确定因素,考虑作战任务收益和航行油耗这两个目标,建立了不确定无人机双目标任务分配模型;其次,根据不确定变量的数字特征定义了期望值-标准差有效解,并把原不确定双目标模型转化为确定多目标任务分配模型;然后,通过线性加权法与理想点法将其转化为单目标优化问题进而设计算法求解;最后,建立4架无人机,24个敌方目标的任务实例,利用蚁群算法进行求解,得到了期望值-标准差有效任务分配方案。实例仿真结果表明,该求解方法能够有效地处理不确定环境下无人机任务分配问题,且任务分配次序规划合理,总代价较小。

Based on the uncertainty theory, this paper studied the multi-target assignment of UAV in an uncertain environment. Firstly, the uncertainty factors in the task allocation planning were described by uncertain variables, and the dual-target task allocation model of uncertain UAV was established considering the two targets of combat mission income and flight fuel consumption. Secondly, the expected value-standard deviation effective solution was defined according to the numerical characteristics of uncertain variables, and the original uncertain two-objective problem was transformed into a definite multi-objective task assignment planning problem. Thirdly, it was transformed into a single objective optimization problem by the ideal point method and the linear weighting method. Finally, the task examples of 4 UAVs and 24 enemy targets were set up. The ant colony algorithm was utilized to solve the problem and the optimal task assignment scheme was obtained. The simulation results show that this method can effectively deal with the task assignment problem of UAV in an uncertain environment, and the task assignment order planning is reasonable, and the total cost is small.