时序耦合约束下的多无人机协同任务决策研究
Collaborative Task Assignment for Multi-UAV with Sequence and Time Constrains

针对多无人机协同执行压制敌防空系统任务时各任务间所具有的特定时序耦合约束，建立相应的异构多无人机协同任务决策模型，提出了一种基于遗传算子的混合引力遗传搜索算法（GSA-GA）来进行问题求解，针对任务之间的时序耦合约束特点，设计了相应的编解码模式，融合遗传算法特有的交叉、变异操作算子对GSA-GA中的个体进行最优解搜索，仿真结果表明该算法能够有效地解决具有时序耦合约束时的多异构无人机协同任务决策问题。通过与传统DPSO算法进行对比分析，不仅具有明显的性能提升，且算法的编解码更易于操作，从而为无人机执行具有时序耦合约束任务时的协同任务分配问题提供了科学的决策依据。
In this paper, based on task sequence and time constraint in the SEAD mission of multi-UAV, a heterogeneous multi-UAV cooperative task assignment mathematical model is established. We put forward a hybrid algorithm GSA-GA(gravity search algorithm-genetic algorithm) to resolve cooperative task assignment. The algorithm combines gravity search algorithm and genetic algorithm, improves the coding and decoding methods in updating the position. The simulation result shows that the GSA-GA has rapid convergence rate in solving the cooperative task assignment compared with the classic DPSO algorithm, and has the better resolution