风扰动下多Agent自适应间隔控制方法  

Multi-agent adaptive interval management under wind disturbance

作　　者：魏志强[1] 商谢睿 王晶 WEI Zhiqiang;SHANG Xierui;WANG Jing(College of Air Traffic Management,CAUC,Tianjin 300300,China)

机构地区：[1]中国民航大学空中交通管理学院,天津300300

出　　处：《飞行力学》2023年第6期27-35,共9页Flight Dynamics

基　　金：国家自然科学基金资助(U2133210);中央高校基本科研任务费项目资助(3122021066);波音基金项目资助(20221010014)。

摘　　要：为避免航路风在民航客机飞行中带来的额外冲突风险,确保飞行安全,首先建立了风扰动下的四维航迹模型;然后建立了基于时间偏差的飞行间隔管理模型及Agent自适应间隔管理模型,设计了速度剖面调节规则;之后针对速度剖面优化建立了目标函数模型,包括速度剖面偏差值与燃油消耗值;随后建立基于优化速度剖面的间隔控制模型,根据速度剖面特点设计编码方式,改进粒子群遗传算法优化出新的速度剖面;最后在基础场景下进行仿真验证。仿真结果表明,所采用的间隔控制方法能确保飞行到达风险区域的时刻符合要求的同时达到最优目标值,且改进的粒子群遗传算法相比单纯粒子群算法有更高运算效率。In order to solve the extra conflict risk in flight of aircraft brought by track wind and to ensure the air safety,the four-dimensional trajectory model under the condition of wind disturbance was established firstly.Secondly,the flight interval management model based on the time deviation and Agent self-adaptive interval management model was established,and speed profile regulating rules were designed.Thirdly,the objective function model was established for speed profile optimization,including speed profile deviation value and fuel consumption value.Fourthly,the conflict resolution model based on optimized speed profile was established.According to the characteristics of speed profile,the coding method was designed,and the particle swarm genetic algorithm was improved to optimize the new speed profile.Finally,the simulation verification was done in the basic scene.The simulation results show that the described conflict resolution method can ensure that the time of flying to the risky area meets requirements and achieves the optimal target value,and the improved particle swarm genetic algorithm shows better calculation effect than that of simple particle swarm algorithm.

关 键 词：空中交通管理 自主间隔控制 四维航迹 飞行剖面 粒子群遗传算法 

分 类 号：V355[航空宇航科学与技术—人机与环境工程]