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基于微分Petri网的民机航迹演化通用模型构建 被引量:4

Construction of Civil Aircraft Trajectory Evolution General Model Based on Differential Petri-Net
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摘要 为实现对未来大流量、高密度、小间隔条件下的空域实施管理,在战略航迹规划阶段,提出了一种模块化的战略航迹演化通用模型。建立了不同航段之间航空器状态动态切换的一类宏观Petri网演化模型,以及同一航段内航空器速度和高度两种特征参数值连续变化的3类微观Petri网演化模型。根据航空器特征参数值转化的4种不同形式并基于航空器全飞行剖面的混杂运行特性,运用微分Petri网理论,定义了航空器的4种演化模式,通过组合各种演化模式得到了3种航空器基本演化模型。在满足航空器性能约束的前提下,通过设定10个航段及15个高度和速度预设值,得到了全飞行剖面下各特征参数的演化图。结果表明,所设计的演化模型增强了航迹预测模型的通用性,能够反映航空器在水平剖面和垂直剖面内的状态变化。 To resolve the problem of future airspace management under the condition of great traffic flow, high density, and small separation, a modular evolution model is built during the process of air- craft trajectory strategic planning. A state switch macroscopic Petri-net evolution model and three mi- crocosmic Petri-net evolution models accompanied with the continuous change of aircraft speed and height in the same segment based on the aerodynamics models are presented. According to the different forms of aircraft characteristic parameter conversion and the hybrid evolution characteristics, four evolu- tion models using differential Petri-net theory and three evolution modes using the combination of vari- ous evolution models are defined. The 4-D trajectory evolution graphs with aircraft performance con- straints can be obtained by setting 10 flight segments and 15 defaults of height and speed. Theoretical a- nalysis and simulation results demonstrate that the proposed models can enhance the versatility of trajectory prediction model and reflect the aircraft horizontal and vertical trajectory profiles precisely.
出处 《南京航空航天大学学报》 EI CAS CSCD 北大核心 2014年第2期322-328,共7页 Journal of Nanjing University of Aeronautics & Astronautics
基金 国家自然科学基金(61174180 71271113)资助项目 江苏省自然科学基金(BK2010502)资助项目 江苏省产学研联合创新资金-前瞻性联合研究(BY2012014)资助项目 江苏省普通高校研究生科研创新计划(CXLX11-0210)资助项目 中国博士后科学基金(2014M550291)资助项目
关键词 空中交通管制 航迹预测 演化模型 混杂PETRI网 微分Petri网 air traffic control trajectory prediction evolution model hybrid Petri-net differential Petrinets
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参考文献14

  • 1汤新民,韩云祥,韩松臣.基于混杂系统模型的航空器4D航迹推测[J].南京航空航天大学学报,2012,44(1):105-112. 被引量:17
  • 2伊群.美国新一代空中交通管理系统运行概念[J].中国民用航空,2007(8):27-31. 被引量:16
  • 3吴鹍,潘薇.基于数据挖掘的四维飞行轨迹预测模型[J].计算机应用,2007,27(11):2637-2639. 被引量:39
  • 4Wu Kun, Pan Wei. A 4-D trajectory prediction model based on radar data[C]// Proceedings of the 27th Chinese Control Conference. Kunming: IEEE, 2008: 591-594.
  • 5Lin Xi, Zhang Jun, Zhu Yanbo, et al. Simulation study of algorithms for aircraft trajectory prediction based on ADS-B technology[C]//ASIA Simulation Conferenee-Tth International Conference on System Simulation and Scientific Computing. Beijing: IEEE, 2008: 322-327.
  • 6Gong C, McNally D. A methodology for automated trajectory prediction analysis[C]// AIAA Guidance, Navigation, and Control Conference. Providence, RI: AIAA, 2004:1-14.
  • 7Slattery R A, Zhao Yiyuan. En-route descent trajec- tory synthesis for air traffic control automation I-C]// Proceedings of the American Control Conference. Se- attle: IEEE, 1995: 3430-3434.
  • 8Slattery R A. Terminal area trajectory synthesis for air traffic control automation[C]//Proceedings of the American Control Conference. Seattle: IEEE, 1995: 1206-1210.
  • 9Prevot T, Leei P, Smith N, et al. ATC technologies for controller-managed and autonomous flight operations[C]//AIAA Guidance, Navigation, and Control Conference. San Francisco: AIAA, 2005 : 1-43.
  • 10Robinson J E, Isaacson D R. Development of a closed-loop testing method for a next-generation ter- minal area automation system[C]// Proceedings o{ the American Control Conference. Anchorage, AK: IEEE, 2002: 1325-1330.

二级参考文献22

  • 1吴树范,郭锁凤.基于四维导引的飞机纵向飞行剖面的解算与综合[J].航空学报,1993,14(5). 被引量:12
  • 2Harry S, Richard B, Michael L. Next generation air transportation system(NGATS) air traffic manage- ment (ATM)--airspace project [R]. NASA, 2006 25-28.
  • 3Olaf D, Thorsten A, Cristiano B, et al. SESAR D3 ATM target concept [R]. DLM-0612-001-02-00a. Toulouse: Eurocontrol, 2007.. 1-17.
  • 4Anthony W. Trajectory prediction concepts for next generation air traffic management [C]//3rd USA/ Europe Air Traffic Management R &- D Seminar. Napoli: Eurocontrol, 2000: 1-10.
  • 5Prevost C G, Desbiens A, Gagnon E. Extended Kalman filter for state estimation and trajectory pre- diction of a moving object detected by an unmanned aerial vehicle [C]//American Control Conference. New York: IEEE,2007:1805-1810.
  • 6Lymperopoulos I, Lygeros J. Sequential Monte Car- lo methods for multi-aircraft trajectory prediction in air traffic management [J]. International Journal of Adaptive Control and Signal Processing, 2010, 24 (10) : 830-849.
  • 7Slattery R, Zhao Y. Trajectory synthesis for air traffic automation[J]. Journal of Guidance, Control and Dynamics, 1997, 20(2): 232-238.
  • 8Richard A C. Climb trajectory prediction enhance- ment using airline flight planning information[C]// Proceedings of the AIAA Guidance, Navigation, and Control Conference. Portand: AIAA, 1999: 1077- 1087.
  • 9Lee H P, Leffer M F. Development of the L-1011 four-dimensional flight management system, NASACR 3700[R]. NASA,1984.. 1-135.
  • 10Chester G, William N C. Using flight manual data to derive aero-propulsive models for predicting air- craft trajectories [C]//AIAA Aircraft Technology, Integration, and Operations(ATIO) 2002 Technical. California: AIAA, 2002: 1-7.

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