具有周期性双层优化结构的无人机集群航路规划模型

Route planning of UAV cluster via periodic bilevel optimization

针对多种威胁条件下的无人机集群航路规划问题,提出了集群控制方法和周期性双层优化算法。以定点抵达任务为背景,将d-范数、冲击函数与反曲函数结合起来,构建了能够实现雷诺兹准则的集群动态控制模型,并采用设计出的周期性双层优化算法求解中心无人机的航路规划问题。通过仿真算例,验证了该模型的实效性和优化算法的可行性,与遗传算法-人工势场混合算法相比,周期性双层优化算法求解效率更高且优化效果更好。

Aiming at route planning of UAV cluster under various threats, this paper proposes a cluster control method and periodic bilevel optimization algorithm. Based on a fixed-point arrival mission, a cluster dynamic control model is constructed by combining d-norm,impact function and inverse function, which can realize Reynolds rules. A periodic bilevel optimization algorithm is designed to solve the route planning problem of central UAV. Eeffectiveness of the model and feasibility of the optimization algorithm are verified by simulation examples. Compared with the hybrid genetic algorithm ie. artificial potential field algorithm, the periodic bilevel optimization algorithm has a higher efficiency and better optimization effect.