基于协同进化的复杂低空下多飞行器协同航迹规划方法

发布时间：2018-01-25 02:56

本文关键词： 复杂低空多飞行器多目标进化算法路径规划　出处：《南京航空航天大学学报》2017年S1期 　论文类型：期刊论文

【摘要】：由于低空空域环境复杂,威胁通用航空器运行安全。复杂低空多飞行器航迹规划方法是保障安全、提高效率的关键技术。在特定空域范围内,依据地形特点、环境威胁以及飞行器自身物理条件等约束和安全效率等性能指标,为飞行器规划出最优航迹。然而,多飞行器的航迹规划问题存在多约束、强耦合、多目标等难点,现有方法缺乏对问题先验知识的挖掘和利用,导致难以兼顾安全与效率。针对多飞行器航迹规划问题,建立了多飞行器航迹优化多目标模型。为了进一步提升优化效率,基于启发式算子的自适应差分多目标进化算法,引入多种群协同进化,每个飞行器通过不同种群独立进化,建立合作机制提升种群进化质量,避免陷入极值。最后通过二维与三维仿真实验验证了算法的可行性和有效性。
[Abstract]:Because of the complexity of the low-altitude airspace environment, it threatens the safety of general purpose aircraft. The track planning method of complex low-altitude multi-aircraft is the key technology to ensure the safety and improve the efficiency. In the specific airspace range, according to the characteristics of the terrain. Environmental threats, physical conditions of aircraft and other performance indicators such as safety efficiency and other constraints, planning the optimal trajectory for aircraft. However, there are multiple constraints and strong coupling for multi-vehicle trajectory planning problem. Due to the lack of prior knowledge mining and utilization, it is difficult to take safety and efficiency into account. In order to further improve the optimization efficiency, an adaptive differential multi-objective evolutionary algorithm based on heuristic operator is proposed, and multi-group co-evolution is introduced. By independent evolution of different populations, each vehicle establishes a cooperative mechanism to improve the quality of population evolution and avoid falling into extremum. Finally, the feasibility and effectiveness of the algorithm are verified by two-dimensional and three-dimensional simulation experiments.
【作者单位】：中国民航管理干部学院通用航空系;
【基金】：国家自然科学基金民航联合基金(U1533119)资助项目
【分类号】：V328.3
【正文快照】： 引用格式:管祥民,吕人力.基于协同进化的复杂低空下多飞行器协同航迹规划方法[J].南京航空航天大学学报,2017,49(S):89-95.GUAN Xiangmin,L媲Renli.Complex low-altitude airspace multi-aircraft cooperation path planning meth-od based on cooperative coevolutionary[J].

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