宇航学报

宇航学报 ›› 2020, Vol. 41 ›› Issue (5): 507-520.doi: 10.3873/j.issn.1000-1328.2020.05.001

• 飞行器设计与力学 • 上一篇    下一篇

吸气式高超声速飞行器爬升段关键任务点的鲁棒优化

汤佳骏，刘燕斌，曹瑞，陆宇平，朱鸿绪，衣春轮   

  1. 1. 南京航空航天大学自动化学院， 南京 210016； 2. 南京航空航天大学航天学院， 南京 210016；
    3. 北京航空航天大学虚拟现实技术与系统国家重点实验室， 北京 100191
  • 收稿日期:2019-09-17 修回日期:2019-12-13 出版日期:2020-05-15 发布日期:2020-05-25
  • 基金资助:
    国家自然科学基金（11572149）；南京航空航天大学研究生创新基地（实验室）开放基金项目（kfjj20180311）；虚拟现实技术与系统国家重点实验室开放基金(VRLAB2018C04)

Robust Optimization of Key Mission Points in Climbing Phase for Air Breathing Hypersonic Vehicle#br#

TANG Jia jun, LIU Yan bin, CAO Rui, LU Yu ping, ZHU Hong xu, YI Chun lun   

  1. 1. College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China; 2. College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China; 3. State Key Laboratory of Virtual Technology and Systems, Beijing University of Aeronautics and Astronautics, Beijing 100191, China
  • Received:2019-09-17 Revised:2019-12-13 Online:2020-05-15 Published:2020-05-25

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摘要： 针对吸气式高超声速飞行器爬升段飞行任务，考虑飞行器气动/推进特性及参数不确定性问题，采用鲁棒优化思路，结合巡航性能指标，优选了飞行器爬升段的关键任务点。首先，由能量状态法结合发动机工作约束，确定了飞行器的爬升起始任务点；其次，依据飞行器巡航性能分析方法，提出了兼顾气动/推进效率的性能指标，优化得到了高超声速飞行器爬升末端任务点；最后考虑飞行器质心位置的不确定性，采用鲁棒优化方法确定了爬升段末端的飞行任务窗口。仿真结果表明，设计的优选流程快速可行，飞行任务窗口能同时满足飞行器的巡航飞行性能要求及不确定性最坏情况的约束，具有较强的鲁棒性。

关键词: 吸气式高超声速飞行器, 爬升段飞行任务, 参数化模型, 鲁棒优化, 飞行控制

Abstract: The key mission points in the climbing phase of an air-breathing hypersonic vehicle, considering the aerodynamic/propulsion characteristics and parameter uncertainty of the vehicle in the flight mission, are optimally selected in this paper. The robust optimization idea, combined with the cruise performance index, is feasible for the optimal selection. Firstly, the energy-state analysis is combined with the engine constraints to determine the initial mission point for climbing. Then, according to the cruise performance analysis of the vehicle, the performance index of the aerodynamic/propulsion efficiency is proposed to optimize the end mission point for climbing. Finally, the mission window at the end of the climbing is determined by the robust optimization, considering the uncertainty of the centroid position of the air-breathing hypersonic vehicle. The simulation results illustrate that the optimal selection process is fast and feasible. Meanwhile, the mission window satisfies both the cruise performance requirements of the air-breathing hypersonic vehicle and the worst case constraints of uncertainty, which has strong robustness.

Key words: Air-breathing hypersonic vehicle, Climbing phase, Parametric model, Robust optimization, Flight control

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