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风影响下航空器多目标最优控制航迹优化方法

常哲宁 胡明华 张颖 杨磊 邹润原

吕善伟, 吴东梅, 王伟, 等 . 射电天文望远镜的焦面阵设计[J]. 北京航空航天大学学报, 2007, 33(03): 341-344.
引用本文: 常哲宁,胡明华,张颖,等. 风影响下航空器多目标最优控制航迹优化方法[J]. 北京航空航天大学学报,2024,50(11):3521-3531 doi: 10.13700/j.bh.1001-5965.2022.0836
Lü Shanwei, Wu Dongmei, Wang Wei, et al. Design of focal plane array of radio telescope[J]. Journal of Beijing University of Aeronautics and Astronautics, 2007, 33(03): 341-344. (in Chinese)
Citation: CHANG Z N,HU M H,ZHANG Y,et al. A multi-objective optimal control trajectory optimization method for aircraft under wind influence[J]. Journal of Beijing University of Aeronautics and Astronautics,2024,50(11):3521-3531 (in Chinese) doi: 10.13700/j.bh.1001-5965.2022.0836

风影响下航空器多目标最优控制航迹优化方法

doi: 10.13700/j.bh.1001-5965.2022.0836
基金项目: 国家自然科学基金(61903187); 江苏省自然科学基金(BK20190414); 工信部中欧航空科技合作项目(MJ-2020-S-03)
详细信息
    通讯作者:

    E-mail:yoyozhying@163.com

  • 中图分类号: V355;TB553

A multi-objective optimal control trajectory optimization method for aircraft under wind influence

Funds: National Natural Science Foundation of China (61903187); Natural Science Foundation of Jiangsu Province (BK20190414); China-EU Aviation Science and Technology Cooperation Project of the Ministry of Industry and Information Technology (MJ-2020-S-03)
More Information
  • 摘要:

    风影响下的四维航迹优化问题约束复杂,多目标四维航迹优化模型难以求解。基于最优控制方法研究固定水平航路下考虑风影响的航迹垂直剖面多目标优化问题的建模和求解。以飞行时间和飞行油耗最小化为双目标建立航迹最优控制模型;设计了梯形配点结合ε-约束方法的模型求解方法,并针对按高度层飞行场景下的航迹优化提出两阶段求解方法;建立了四维航迹仿真模型用于对轨迹优化效果的仿真验证;选用长航线实际飞行计划数据作为算例进行算法性能分析,并区分自由高度飞行和按高度层飞行2种场景进行航迹优化效果验证。实验结果表明:所提模型和所提方法相比其他2种常用算法能获得更优的Pareto前沿解,按高度层飞行场景下采用所提方法能获得更优的前沿解;自由高度飞行和按高度层飞行2种场景下求得的前沿解中最小燃油耗航迹分别比飞行计划仿真航迹的油耗降低了6.33%和5.94%,最短飞行时间航迹分别比飞行计划仿真航迹的飞行时间降低了10.16%和10.01%。

     

  • 图 1  四维航迹优化模型框架

    Figure 1.  Framework of 4D trajectory optimization model

    图 2  侧风对航迹的影响

    Figure 2.  Influence of crosswind on trajectory

    图 3  航迹仿真模型整体框架

    Figure 3.  Framework of trajectory simulation modeling

    图 4  航迹仿真推演计算流程

    Figure 4.  Flow of calculation process of trajectory simulation derivation

    图 5  VHHH-EHAM航线及高空风

    Figure 5.  VHHH-EHAM flight route and high-altitude wind

    图 6  ECMWF预报风与实际风对比

    Figure 6.  Comparison of wind forecast by ECMWF and actual wind

    图 7  航班计划四维航迹仿真结果

    Figure 7.  4D trajectory simulation results of flight plan

    图 8  3类算法帕累托前沿对比

    Figure 8.  Comparison of Pareto frontier of three types of algorithms

    图 9  KLM888航班航迹优化Pareto前沿解

    Figure 9.  Pareto frontier solution of trajectory optimization for flight KLM888

    图 10  自由高度飞行最优航迹剖面对比

    Figure 10.  Comparison of optimal trajectory profiles for flight at free altitude

    图 11  按高度层飞行最优航迹剖面对比

    Figure 11.  Comparison of optimal trajectory profiles for flight by altitude layer

    表  1  3类算法性能对比

    Table  1.   Comparison of performance of three types of algorithms

    算法 CM HV MID
    ε-约束 1 0.0109 13.1272
    NSGA-Ⅱ 0 0.0050 107.5931
    CI线性加权 0 0.0002 105.2507
    下载: 导出CSV

    表  2  高度层约束场景算法性能对比

    Table  2.   Comparison of performance of algorithms under altitude layer constraint

    算法 CM HV MID
    两阶段求解 1 0.0107 13.1608
    直接求解(初始解1) 0 0.0013 33.6483
    直接求解(初始解2) 0 0.0028 251.6432
    直接求解(初始解3) 0 0.0014 32.5157
    下载: 导出CSV

    表  3  KLM888航班四维航迹优化结果对比

    Table  3.   Comparison of 4D trajectory optimization results for flight KLM888

    航迹 飞行时间/min 燃油消耗/kg
    自由高度飞行最短飞行时间航迹 610 132 145
    自由高度飞行最小燃油消耗航迹 669.5 111 396
    按高度层飞行最短飞行时间航迹 611 127 197
    按高度层飞行最小燃油消耗航迹 655.5 111 858
    航班计划仿真航迹 679 118 920
    下载: 导出CSV
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  • 收稿日期:  2022-10-04
  • 录用日期:  2022-11-28
  • 网络出版日期:  2023-01-17
  • 整期出版日期:  2024-11-30

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