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论文:2022,Vol:40,Issue(3):618-627 |
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引用本文： |
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王健磊, 陈晓宇, 洪厚全, 李春娜, 龚春林, 付俊兴. 基于变精度模型的变外形飞行器弹道优化[J]. 西北工业大学学报 |
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WANG Jianlei, CHEN Xiaoyu, HONG Houquan, LI Chunna, GONG Chunlin, FU Junxin. Trajectory optimization of morphing aircraft based on multi-fidelity model[J]. Northwestern polytechnical university |
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| 基于变精度模型的变外形飞行器弹道优化 |
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| 王健磊1, 陈晓宇1, 洪厚全2, 李春娜1, 龚春林1, 付俊兴2 |
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1. 西北工业大学 航天学院, 陕西 西安 710072;
2. 江西洪都航空工业集团有限责任公司, 江西 南昌 330024 |
| 摘要: |
| 变外形飞行器在飞行过程中可以根据需要灵活改变自身的气动外形以适应飞行条件的变化,与传统的固定外形飞行器相比,具有非常明显的优势。针对一种机翼后掠角和轴向位置可改变的变外形飞行器,提出了基于变精度模型的求解流程,并对其最优弹道和变形规律进行了研究。将攻角、马赫数、后掠角和机翼轴向位置定义为生成训练数据的变量,建立了满足精度条件的变精度Kriging模型来预测飞行器的气动性能。将该模型作为hp自适应伪谱法的气动输入,建立了变形规律优化求解流程,并分别对固定翼飞行器和变外形飞行器以最少燃料消耗为目标进行弹道优化。在满足飞行任务要求的同时,实现了变形参数、攻角和发动机控制参数等控制量的同时优化,结果表明变外形飞行器的爬升、下降效率较高,最优弹道具有明显的优势。同时,所提出的研究流程具有通用性,可以有效降低变外形飞行器的CFD计算成本,提高变外形飞行器弹道优化效率。 |
| 关键词:
变外形飞行器
变精度模型
弹道优化
hp自适应伪谱法
变形规律
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| Trajectory optimization of morphing aircraft based on multi-fidelity model |
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| WANG Jianlei1, CHEN Xiaoyu1, HONG Houquan2, LI Chunna1, GONG Chunlin1, FU Junxin2 |
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1. School of Astronautics, Northwestern Polytechnical University, Xi'an 710072, China;
2. Jiangxi Hongdu Aviation Industry Group Co., Ltd, Nanchang 330024, China |
| Abstract: |
| Morphing aircraft can flexibly change its aerodynamic shape to adapt to the varying flight conditions during a flight. Compared with the traditional fixed shape aircraft, it has a very obvious advantage. This paper proposed a solution flow based on the multi-fidelity model for the morphing aircraft with morphing wings, and the optimal trajectory and morphing rules are studied. The angle of attack, Mach number, sweep angle and axial position of the morphing wing are defined as variables for generating training data for building the multi-fidelity Kriging model, which is used to predict the aerodynamic performance of the aircraft. Based on the hp-adaptive pseudospectral method, the model is used as aerodynamic input to establish the optimization process of morphing rules, and the trajectory optimization is carried out for the contrast fixed wing aircraft and morphing aircraft with the goal of minimum fuel consumption, respectively. The control parameters such as morphing parameters, angle of attack and engine control parameters are optimized simultaneously while meeting the flight mission requirements. The results show that the morphing aircraft has higher climbing and descending efficiency, and the optimal trajectory has obvious advantages. Moreover, the research flow proposed in this paper is universal, which can effectively reduce the CFD calculation cost and improve the efficiency of trajectory optimization of the variable shape vehicle. |
| Key words:
morphing aircraft
multi-fidelity model
trajectory optimization
hp-adaptive pseudospectral method
morphing rules
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| 收稿日期: 2021-06-18
修回日期:
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| DOI: 10.1051/jnwpu/20224030618 |
| 通讯作者: 龚春林(1980—),西北工业大学教授、博士生导师,主要从事导弹和先进空天飞行器总体设计、飞行器多学科设计优化研究。e-mail:Leonwood@nwpu.edu.cn
Email：Leonwood@nwpu.edu.cn |
| 作者简介: 王健磊(1983—),西北工业大学助理研究员,主要从事流体力学、飞行器设计研究。
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参考文献: |
|
|
[1] OLIVIU S G, KOREANSCHI A, BOTEZ R M. A new non-linear vortex lattice method: applications to wing aerodynamic optimizations[J]. Chinese Journal of Aeronautics, 2016, 29(5):1178-1195
[2] KOREANSCHI A, GABOR O S, ACOTTO J. Optimization and design of an aircraft's morphing wing-tip demonstrator for drag reduction at low speed, part Ⅰ-aerodynamic optimization using genetic, bee colony and gradient descent algorithms[J]. Chinese Journal of Aeronautics, 2017, 30(1): 149-163
[3] KOREANSCHI A, GABOR O S, ACOTTO J. Optimization and design of an aircraft's morphing wing-tip demonstrator for drag reduction at low speeds, part Ⅱ-experimental validation using infra-red transition measurement from wind tunnel tests[J]. Chinese Journal of Aeronautics, 2017, 30(1): 164-174
[4] 吕吉婵, 董彦非, 陈元恺. 中低空高度下变后掠翼的最佳变后掠规律[J]. 飞行力学, 2016, 34(2):24-27 LYU Jichan, DONG Yanfei, CHEN Yuankai. Rules of the optimal variable sweep wing in low and medium height[J]. Flight Dynamics, 2016, 32(2): 24-27 (in Chinese)
[5] 刘璐, 董彦非. 基于空气动力学的变后掠翼翼身组合体变后掠规律基础研究[J]. 重庆理工大学学报, 2017, 31(8): 76-80 LIU Lu, DONG Yanfei. Basic analysis of the best sweep variation rule about variable sweep wing-body based on aerodynamics[J]. Journal of Chongqing University of Technology, 2017, 31(8): 76-80 (in Chinese)
[6] LEE I, CHOI K, ZHAO L. Sampling-based RBDO using the dynamic Kriging (d-Kriging) method and stochastic sensitivity analysis[J]. Structural & Multidisciplinary Optimization, 2010, 44(3): 299-317
[7] ALLAIRE D K. Surrogate modeling for uncertainty assessment with application to aviation environmental system models[J]. AIAA Journal, 2010, 48(8): 1791-1791
[8] 王方鹏, 罗竑, 王海鹏. 一种滑翔飞行器弹道的参数优化方法研究[J]. 航空制造技术, 2015(增刊1): 104-107 WANG Fangpeng, LUO Hong, WANG Haipeng. Research on parameter optimization method of air vehicle gliding trajectory[J]. Aeronautical Manufacturing Technology, 2015(suppl 1): 104-107 (in Chinese)
[9] 黄国强, 陆宇平, 南英. 飞行器轨迹优化数值算法综述[J]. 中国科学:技术科学, 2012, 42(9): 1016-1036 HUANG Guoqiang, LU Yuping, NAN Ying. A survey of numerical algorithms for trajectory optimization of flight vehicles[J]. Scientia Sinica(Technologica), 2012, 42(9): 1016-1036 (in Chinese)
[10] 李伟明, 孙瑞胜, 吴军基. 变后掠翼航弹滑翔弹道优化设计[J]. 弹道学报, 2012, 24(2): 6-9 LI Weiming, SUN Ruisheng, WU Junji. Optimization of glide trajectory for aerial bomb with morphing swept wings[J]. Journal of Ballistics, 2012, 24(2): 6-9 (in Chinese)
[11] 郭杰, 唐胜景, 李响, 等. 基于改进粒子群算法的方案飞行弹道优化设计[J]. 北京理工大学学报, 2010, 30(6): 682-692 GUO Jie, TANG Shengjing, LI Xiang, et al. Optimum design of the project trajectory based on an improved particle swarm optimization[J]. Transactions of Beijing Institute of Technology, 2010, 30(6): 682-692 (in Chinese)
[12] 龚春林, 赤丰华, 谷良贤, 等. 基于Karhunen-Loève展开的分布式变体飞行器最优控制方法[J]. 航空学报, 2018, 39(2):121518 GONG Chunlin, CHI Fenghua, GU Liangxian, et al. Optimal control method for distributed morphing aircraft based on Karhunen-Loève expansion[J]. Acta Aeronautica et Astronautica Sinica, 2018, 39(2): 121518 (in Chinese)
[13] 王娜, 陈洁卿, 明超, 等. 基于hp自适应伪谱法的变后掠翼导弹弹道优化设计[J]. 弹道学报, 2016(4): 24-29 WANG Na, CHEN Jieqing, MING Chao, et al. Optimization design for trajectory of morphing-wing missile based on hp-adaptive pseudo-spectral method[J]. Journal of Ballistics, 2016(4): 24-29 (in Chinese)
[14] TOAL J. Some considerations regarding the use of multi-fidelity Kriging in the construction of surrogate models[J]. Structural and Multidisciplinary Optimization 2015, 51(6): 1223-1245
[15] ZAHIR M K, GAO Zhenghong. Variable-fidelity optimization with design space reduction[J]. Chinese Journal of Aeronautics, 2013(4): 14-22
[16] HUANG Likeng, GAO Zhenghong, ZHANG Dehu. Research on multi-fidelity aerodynamic optimization methods[J]. Chinese Journal of Aeronautics, 2013,26(2): 279-286
[17] HU Jiexiang, ZHOU Qi, JIANG Ping, et al. An adaptive sampling method for variable-fidelity surrogate models using improved hierarchical Kriging[J]. Engineering Optimization, 2017(3): 1-19
[18] YIN Shi, ZHU Ming, LIANG Haoquan. Multi-disciplinary design optimization with variable complexity modeling for a stratosphere airship[J]. Chinese Journal of Aeronautics, 2019, 32(5): 191-202
[19] KOZIEL S, TESFAHUNEGN Y, LEIFSSON L. Variable-fidelity CFD models and co-Kriging for expedited multi-objective aerodynamic design optimization[J]. Engineering Computations, 2016, 33(8): 2320-2338
[20] LE L G. Multi-fidelity Gaussian process regression for computer experiments[D]. Autres: Université Paris-Diderot-Paris VII, 2013
[21] 韩忠华. Kriging模型及代理优化算法研究进展[J]. 航空学报, 2016, 37(11): 3197-3225 HAN Zhonghua. Kriging surrogate model and its application to design optimization: a review of recent progress[J]. Acta Aeronautica et Astronautica Sinica, 2016, 37(11): 3197-3225 (in Chinese)
[22] HAN Zhonghua, XU Chenzhou, ZHANG Liang, et al. Efficient aerodynamic shape optimization using variable-fidelity surrogate models and multilevel computational grids[J]. Chinese Journal of Aeronautics, 2020, 33(1): 31-47
[23] ZHANG Keshi, HAN Zhonghua, GAO Zhongjian, et al. Constraint aggregation for large number of constraints in wing surrogate-based optimization[J]. J Structural and Multidisciplinary Optimization, 2019, 59(2): 421-438
[24] 李春娜, 张阳康. 一种适用于气动优化的高效自适应全局优化方法[J]. 航空学报, 2020, 41(5): 95-107 LI Chunna, ZHANG Yangkang. An efficient adaptive global optimization method suitable for aerodynamic optimization[J]. Acta Aeronautica et Astronautica Sinica, 2020, 41(5): 95-107 (in Chinese)
[25] KRIGE D G. A statistical approach to some basic mine valuation problems on the witwatersrand[J]. Journal of the Southern African Institute of Mining and Metallurgy, 1951, 52(6): 119-139
[26] LI Chunna. Adaptive optimization methodology based on Kriging modeling and a trust region method[J]. Chinese Journal of Aeronautics 2019, 32(2): 281-295
[27] GANDHI M. Trajectory optimization algorithm studies[J]. Mathematics, 2015,15(2): 267-281
[28] 张博渊, 宗群, 鲁瀚辰, 等. 基于hp自适应伪谱法的四旋翼无人机编队轨迹优化[J]. 科技导报, 2017, 35(7): 69-76 ZHANG Boyuan, ZONG Qun, LU Hanchen, et al. Trajectory optimization of quad-rotor UAV formation using hp-adaptive pseudospectral method[J]. Science & Technology Review, 2017, 35(7): 69-76 (in Chinese)
[29] BOUHLEL M A, HWANG J T, BARTOLI N, et al. A Python surrogate modeling framework with derivatives[J]. Advances in Engineering Software, 2019, 3(5): 9965-9978 |
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