高速飞行器气动控制耦合优化设计方法研究

董超; 潘鑫; 姜璐璐; 陈刚

doi:10.7652/xjtuxb202408020

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高速飞行器气动控制耦合优化设计方法研究

—————————————————————— | 更新时间：2025-07-28

- 高速飞行器气动控制耦合优化设计方法研究
- Aerodynamic Control Coupling Optimization Design Method for High-Speed Vehicles
- 西安交通大学学报 2024年58卷第8期页码：196-204
- 作者机构：
  
  1. 北京航天长征飞行器研究所,北京,100076
  2. 西安交通大学复杂服役环境重大装备结构强度与寿命全国重点实验室,西安,710049
  3. 西安交通大学陕西省先进飞行器服役环境与控制重点实验室,西安,710049
- 作者简介：
  
  : 2023-11-24。作者简介: 董超(1984—),男,研究员
  陈刚(通信作者),男,教授,博士生导师。基金项目: 国家自然科学基金资助项目(92371201, 52192633)
- 基金信息：
  
  : 2023-11-24。作者简介: 董超(1984—),男,研究员;陈刚(通信作者),男,教授,博士生导师。基金项目: 国家自然科学基金资助项目(92371201, 52192633);陕西省杰出青年科学基金资助项目(2022JC-03)。
- DOI：10.7652/xjtuxb202408020
  中图分类号： V221.8
- 纸质出版：2024
- 稿件说明：
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董超, 潘鑫, 姜璐璐, 等. 高速飞行器气动控制耦合优化设计方法研究[J]. 西安交通大学学报, 2024,58(8):196-204.

DONG Chao, PAN Xin, JIANG Lulu, et al. Aerodynamic Control Coupling Optimization Design Method for High-Speed Vehicles[J]. 2024, 58(8): 196-204.
董超, 潘鑫, 姜璐璐, 等. 高速飞行器气动控制耦合优化设计方法研究[J]. 西安交通大学学报, 2024,58(8):196-204. DOI： 10.7652/xjtuxb202408020.

DONG Chao, PAN Xin, JIANG Lulu, et al. Aerodynamic Control Coupling Optimization Design Method for High-Speed Vehicles[J]. 2024, 58(8): 196-204. DOI： 10.7652/xjtuxb202408020.

摘要

针对传统串行设计过程由于空气动力学和控制系统数学模型复杂、无法综合考虑气动和控制的多目标优化的问题

提出了一种面向高速飞行器气动控制耦合优化设计方法。基于气动单学科代理优化(SBO)算法

将飞行器主动控制技术(ACT)的思想与多学科优化方法(MDO)相结合

构建了高速飞行器气动控制耦合多目标优化流程架构。在2马赫来流条件下

对带有控制舵的双锥体外形开展了气动耦合优化设计研究

以提升飞行器的气动性能和控制能力为优化目标。结果表明:经过气动控制耦合优化后的最优模型在超声速环境下

升力系数和升阻比分别提升了0.401%、2.999%

同时超调量与控制增益分别降低了2.769%、0.655%

气动性能和控制能力得到提升

验证了耦合策略的可行性; 气动控制耦合优化的最优模型不仅使飞行器在超声速工作环境下性能更卓越

还有助于降低后续控制系统的设计难度

提高飞行器设计效率。所提气动控制耦合优化设计方法为高速飞行器的先进设计提供了必要的技术支撑。

Abstract

Due to the complexity of the mathematical models of aerodynamics and control

it is a challenge inherent in the traditional serial design process to fully account for their multi-objective optimization. To address the challenge

a method for aerodynamic control coupling optimization tailored to high-speed vehicles is proposed. Leveraging the surrogate-based optimization(SBO)algorithm

this approach integrates the principles of active control technology(ACT)with multidisciplinary design optimization(MDO)techniques to establish an aerodynamic control coupling multi-objective optimization process for high-speed vehicles. Under Mach 2 flow conditions

aerodynamic control coupling optimization studies are conducted on a double-cone model equipped with control surfaces to enhance the aerodynamic performance and control capability of the vehicles. The results reveal that after aerodynamic control coupling optimization

the optimal model demonstrates a 0.401% increase in lift coefficient and a 2.999% improvement in lift-to-drag ratio in the supersonic environment. Additionally

there is a reduction of 2.769% in overshoot and 0.655% in control gain. These enhancements in aerodynamic performance and control capability affirm the viability of the coupling strategy. Furthermore

the optimal model streamlines subsequent control system design

thereby enhancing overall vehicle design efficiency. The aerodynamic/control coupling optimization design method proposed in this paper serves as crucial technical support for the advanced design of high-speed vehicles.

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references

MAINS R C. Suborbital reusable launch vehicles need reusable research payloads [C]//AIAA SPACE 2011 Conference & Exposition. Reston, VA, USA: AIAA, 2011: 7290.

RICHIE G. The common aero vehicle-space delivery system of the future [C]//Space Technology Conference and Exposition. Reston, VA, USA: AIAA, 1999: 4435.

FIDAN B, MIRMIRANI M, IOANNOU P A. Flight dynamics and control of air-breathing hypersonic vehicles: review and new directions [C]//12th AIAA International Space Planes and Hypersonic Systems and Technologies. Reston, VA, USA: AIAA, 2003: 7081.

KESHMIRI S, COLGREN R, MIRMIRANI M. Development of an aerodynamic database for a generic hypersonic air vehicle [C]//AIAA Guidance, Navigation, and Control Conference and Exhibit. Reston, VA, USA: AIAA, 2005: 6257.

COLGREN R, KESHMIRI S, MIRMIRANI M. Nonlinear ten-degree-of-freedom dynamics model of a generic hypersonic vehicle [J]. Journal of Aircraft, 2009, 46(3): 800-813.

陈功. 升力式再入飞行器气动控制一体化设计方法研究 [D]. 长沙: 国防科技大学, 2020.

吴森堂. 飞行控制系统 [M]. 2版. 北京: 北京航空航天大学出版社, 2013.

庄逢甘, 赵梦熊, 何峻. 航天飞机的随控布局研究: 航天飞机空气动力学问题之六 [J]. 气动实验与测量控制, 1989, 3(1): 1-9.

ZHUANG Fenggan, ZHAO Mengxiong, HE Jun. Applied research of the control configured vehicle design approach to space transportation system [J]. Journal of Experiments in Fluid Mechanics, 1989, 3(1): 1-9.

HALL C E, GALLAHER M W, HENDRIX N D. X-33 attitude control system design for ascent, transition, and entry flight regimes [C]//Guidance, Navigation, and Control Conference and Exhibit. Reston, VA, USA: AIAA, 1998: 4411.

CHAUDHARY A, NGUYEN V, TRAN H, et al. Dynamics and stability and control characteristics of the X-37 [C]//Guidance, Navigation, and Control Conference and Exhibit. Reston, VA, USA: AIAA, 2001: 4383.

张有济. 战术导弹飞行力学设计 [M]. 北京: 宇航出版社, 1998.

CRAMER E J, DENNISJ E J, FRANK P D, et al. Problem formulation for multidisciplinary optimization [J]. SIAM Journal on Optimization, 1994, 4(4): 754-776.

ZANG T A, GREEN L L. Multidisciplinary design optimization techniques -implications and opportunities for fluid dynamics research [C]//30th Fluid Dynamics Conference. Reston, VA, USA: AIAA, 1998: 3798.

DE WECK O, AGTE J, SOBIESZCZANSKI S B, et al. State-of-the-art and future trends in multidisciplinary design optimization [C]//48th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference. Reston, VA, USA: AIAA, 2007: 1905.

余雄庆. 飞机总体多学科设计优化的现状与发展方向 [J]. 南京航空航天大学学报, 2008, 40(4): 417-426.

YU Xiongqing. Multidisciplinary design optimization for aircraft conceptual and preliminary design: status and directions [J]. Journal of Nanjing University of Aeronautics Astronautics, 2008, 40(4): 417-426.

SOBIESZCZANSKI-SOBIESKI J. A linear decomposition method for large optimization problems. Blueprint for development [EB/OL].(1982-02-01)[2023-09-09]. https://ntrs.nasa.gov/search.jsp?R=19820014371.

SOBIESZCZANSKI-SOBIESKI J. Multidisciplinary optimization for engineering systems: achievements and potential [C]//Optimization: Methods and Applications, Possibilities and Limitations. Berlin, Germany: Springer, 1989: 42-62.

PEREZ R E, LIU H H T, BEHDINAN K. Multidisciplinary optimization framework for control-configuration integration in aircraft conceptual design [J]. Journal of Aircraft, 2006, 43(6): 1937-1948.

JEONG S, SUZUKI K, OBAYASHI S, et al. Improvement of nonlinear lateral characteristics of lifting-body type reentry vehicle using optimization algorithm [C]// AIAA Infotech @ Aerospace 2007 Conference and Exhibit. Reston, VA, USA: AIAA, 2007: 2893.

朱广生, 刘文伶. 高超声速轴对称再入机动飞行器气动外形设计与布局研究 [J]. 空气动力学学报, 2016, 34(3): 327-332.ZHU Guangsheng, LIU Wenling. Design for aerodynamic configuration of a hypersonic axisymmetric maneuverable reentry vehicle [J]. Acta Aerodynamica Sinica, 2016, 34(3): 327-332.

National Aeronautics and Space Administration. Earth atmosphere model: metric units [EB/OL]. [2023-04-07]. https://www.grc.nasa.gov/WWW/K-12/airplane/atmosmet.html.

Computational Aerodynamics Institute of China Aerodynamics Research and Development Center. Verification and validation calibration model database: V1.0 [Z]. National Space Science Data Center.

PEREZ R E, LIU H H T, BEHDINAN K. Multidisciplinary optimization framework for control-configuration integration in aircraft conceptual design [J]. Journal of Aircraft, 2006, 43(6): 1937-1948.

MARRISON C I, STENGEL R F. Design of robust control systems for a hypersonic aircraft [J]. Journal of Guidance, Control, and Dynamics, 1998, 21(1): 58-63.

DARVISHPOOR S, ROSHANIAN J, TAYEFI M. A novel concept of VTOL bi-rotor UAV based on moving mass control [J]. Aerospace Science and Technology, 2020, 107: 106238.

NAIDU D S. Optimal control systems [M]. Boca Raton, USA: CRC Press, 2003.

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