AEROSPACE SHANGHAI, Volume. 41, Issue 3, 110(2024)

Multi-objective Approximate Optimization for the Boost-glide Morphing Flight Vehicle Trajectory Scheme

Yiyun ZHAI*... Teng LONG, Zhenyu LIU, Renhe SHI and Nianhui YE |Show fewer author(s)
Author Affiliations
  • School of Aerospace Engineering,Beijing Institute of Technology,Beijing100081,China
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    Figures & Tables(16)
    Schematic diagram of the all-course trajectory for boost-glide morphing flight vehicles
    Optimization framework of the boost-glide morphing flight vehicle trajectory scheme
    Diagram of the nozzle profile
    Flowchart of the Newton iteration method
    Profile of the angle of attack
    Flowchart of the MACO-DE
    Pareto solution set of the boost-glide morphing flight vehicle trajectory scheme
    • Table 1. Segment time of the pitch program angle

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      Table 1. Segment time of the pitch program angle

      参数t1t2t3t4t5
      取值525110122160
    • Table 2. Basic information of the numerical test examples

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      Table 2. Basic information of the numerical test examples

      算例维度nv目标数m约束数nc理论PF数YPF*
      OSY6261 000
      CF182121
      CF2821626
      C2-CDTLZ26211 014
    • Table 3. <bold>Optimization results of the MACO-DE</bold>、<bold>MOEGO</bold>,<bold>and C-MOEA/D </bold>(<bold>IGD values</bold>)

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      Table 3. <bold>Optimization results of the MACO-DE</bold>、<bold>MOEGO</bold>,<bold>and C-MOEA/D </bold>(<bold>IGD values</bold>)

      优化算法IGDOSYCF1CF2C2-CDTLZ2

      MACO-DE

      Nmax=300

      Best10.556 90.127 40.227 60.005 3
      Mean22.093 00.181 50.376 40.035 0
      Worst49.798 30.209 30.545 80.079 1
      Std.16.181 50.032 80.118 90.023 0

      MOEGO

      Nmax=300

      Best40.277 30.176 70.219 20.050 0
      Mean97.865 40.230 80.374 00.064 1
      Worst151.097 30.305 40.538 00.098 9
      Std.36.315 10.043 60.105 50.013 8

      C-MOEA/D

      Nmax=1000

      Best24.999 50.211 30.283 90.058 9
      Mean40.547 40.253 90.388 50.084 4
      Worst73.854 00.278 80.542 00.140 6
      Std.17.403 50.020 10.079 10.028 9
    • Table 4. Launch parameters

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      Table 4. Launch parameters

      参数λ/(°)ϕ/(°)h/kmv/(ms-1)Θ/(°)ψ/(°)
      取值100.0040.000.05090.0090.00
    • Table 5. Boundaries of the control parameters

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      Table 5. Boundaries of the control parameters

      参数αm,min/(°)φ˙c,min/(°)/sχ˙1,min/(°)/sχ¯˙2,min/(s-1)W˙min/(m/s)
      取值0-1-0.135-0.005-0.002 05
      参数αm,max/(°)φ˙c,max/(°)/sχ˙1,max/(°)/sχ¯˙2,max/(s-1)W˙max/(m/s)
      取值2530.1350.0050.002 05
    • Table 6. Parameters of the MACO-DE

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      Table 6. Parameters of the MACO-DE

      参数NInitNglobalNlocalNfeFCR
      取值120424000.80.8
    • Table 7. Comparison of the initial and optimized objectives

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      Table 7. Comparison of the initial and optimized objectives

      参数初始方案优化方案A优化方案B
      起飞质量mtotal/kg48 930.6647 066.9048 869.13
      射程Rtotal/km6 039.096 063.246 438.94
    • Table 8. Comparison of the initial and optimized design variables

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      Table 8. Comparison of the initial and optimized design variables

      参数取值范围初始方案优化方案A优化方案B
      一级装药量mgr1/kg[22 000,24 000]23 00022 090.5223 014.45
      二级装药量mgr2/kg[11 000,13 000]12 00011 173.8112 798.56
      三级装药量mgr3/kg[4 500,6 000]5 5005 503.614 632.45
      高度h1E/km[55,65]6055.2360.65
      当地速度倾角Θ1E/(°)[0,5]34.212.77
      剖面参数vgα1/(m·s-1[4 000,4 500]4 5004 012.714 237.48
      剖面参数vgα2/(m·s-1[3 200,3 700]3 5003 403.053 460.65
      剖面参数αg1/(°)[16,19]1816.3516.03
      剖面参数αg2/(°)[11,15]1212.2411.67
    • Table 9. Comparison of the initial and optimized constraints

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      Table 9. Comparison of the initial and optimized constraints

      参数范围

      初始

      方案

      优化

      方案A

      优化

      方案B

      射程Rtotal/km≥6 0006 039.096 063.246 438.94
      最大高度hmax/km≤7067.2464.4764.44

      攻角动压积αbqb/

      [kPa(°)]

      ≤15096.6396.7498.84
      滑翔段动压qg/kPa≤5046.6044.6735.20
      滑翔段热流Qg/kW≤1 5001 228.631 289.361 271.98
      滑翔段过载ng/g≤31.932.171.94
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    Yiyun ZHAI, Teng LONG, Zhenyu LIU, Renhe SHI, Nianhui YE. Multi-objective Approximate Optimization for the Boost-glide Morphing Flight Vehicle Trajectory Scheme[J]. AEROSPACE SHANGHAI, 2024, 41(3): 110

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    Paper Information

    Category: Innovation and Exploration

    Received: Apr. 11, 2024

    Accepted: --

    Published Online: Sep. 3, 2024

    The Author Email:

    DOI:10.19328/j.cnki.2096-8655.2024.03.012

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