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任务分配是多无人作战飞机(UCAV)协同控制的基础.对此,分析了影响任务分配的关键战技指标,建立了针对攻击任务的多UCAV协同任务分配模型.应用连续粒子群算法对问题进行求解,建立了粒子与实际问题间的映射,通过位置饱和策略构造粒子的搜索空间,采用自适应惯性权重提高粒子群算法的收敛速度和全局寻优能力.考虑到单机的任务载荷限制,引入了买卖合同机制以实现多机任务协调.仿真结果表明,所提出模型和算法可以较好地解决多UCAV协同任务分配问题.
Task assignment is the foundation of cooperative control of UCAV.In this paper, the key tactical and technical indicators that affect mission assignment are analyzed and a multi-UCAV collaborative task assignment model for attack task is established.Using PSO algorithm to solve the problem The mapping between particle and actual problem is established, the search space of particle is constructed by the position saturation strategy, and the adaptive inertia weight is used to improve the convergence speed and global optimization ability of particle swarm optimization.According to the limitation of task load of single machine, The mechanism of contract of sale and purchase is realized to realize the coordination of multi-machine tasks.The simulation results show that the proposed model and algorithm can solve the problem of multi-UCAV cooperative task assignment well.