基于伪谱凸优化和L1罚函数的弹道规划方法研究
Research on Trajectory Programming Method Based on Pseudo-spectral Convex Optimization and L1 Penalty Function
查看参考文献21篇
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文摘
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传统L1惩罚序列凸规划算法(LPSCP)在进行制导炮弹弹道规划时,线性近似误差大,导致目标函数曲线震颤,难以收敛到最优解。针对此问题提出了一种改进的L1惩罚序列凸规划算法(ILPSCP) 。ILPSCP算法引入指数衰减的相对信赖域宽度和带上界的惩罚系数,消除了目标函数的震颤。以一般化控制能量最优轨迹规划模型为研究对象,利用Radau伪谱法离散连续变量,线性凸化非线性动态方程,建立标准凸优化模型。以制导炮弹纵向平面内滑翔弹道模型为仿真实例,分别采用传统的LPSCP算法、提出的ILPSCP算法和非线性最优化通用工具箱GPOPS2 3种方法进行仿真对比。结果表明: ILPSCP算法成功解决了传统LPSCP算法震颤和不稳定等问题;同时ILPSCP算法的仿真结果与GPOPS2的仿真结果高度重合,证明了提出的算法对求解复杂弹道规划问题的有效性。 |
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其他语种文摘
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The traditional L1 penalty sequential convex programming algorithm(LPSCP) has a large linear approximation error in trajectory programming of guided projectiles,which leads to the trembling of the objective function curve,and it is difficult to converge to the optimal solution. Aiming at this problem,an improved L1 penalty sequential convex programming algorithm (ILPSCP) was proposed. The ILPSCP algorithm introduces the relative trust region width of exponential attenuation and the penalty coefficient with upper bound to eliminate the tremor of the objective function. Taking the generalized control energy optimal trajectory programming model as the research object, the Radau pseudo-spectral method was used to discretize the continuous variables and linearly convex the nonlinear dynamic equation to establish the standard convex optimization model. Taking the gliding trajectory model of the guided projectile in the longitudinal plane as an example, the traditional LPSCP algorithm, the proposed ILPSCP algorithm and the general nonlinear optimization toolbox GPOPS2 were used to simulate and compare. The simulation results show that the ILPSCP algorithm successfully solves the problems of chatter and instability of the traditional LPSCP algorithm. At the same time, the simulation results of the ILPSCP algorithm are highly consistent with those of the GPOPS2,which proves the effectiveness of the proposed algorithm in solving complex trajectory programming problems. |
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来源
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弹道学报
,2022,34(1):22-30 【核心库】
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DOI
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10.12115/j.issn.1004-499X(2022)01-004
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关键词
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弹道规划
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凸优化
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Radau伪谱法
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L1罚函数
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地址
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南京理工大学能源与动力工程学院, 江苏, 南京, 210094
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语种
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中文 |
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文献类型
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研究性论文 |
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ISSN
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1004-499X |
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学科
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武器工业 |
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基金
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江苏省自然科学基金
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文献收藏号
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CSCD:7186187
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参考文献 共
21
共2页
|
|
1.
史金光. 制导炮弹滑翔弹道优化设计方法研究.
南京理工大学学报,2011,35(5):610-613,620
|
CSCD被引
7
次
|
|
|
|
|
2.
Tu L H. Reentry skipping trajectory optimization using direct parameter optimization method.
14th AIAA/AHI Space Planes and Hypersonic Systems and Technologies Conference,2006:7993-8006
|
CSCD被引
1
次
|
|
|
|
|
3.
李瑜.
助推-滑翔导弹弹道优化与制导方法研究,2009
|
CSCD被引
11
次
|
|
|
|
|
4.
Fabien B C. Some tools for the direct solution of optimal control problems.
Advances in Engineering Software,1998,29(1):45-61
|
CSCD被引
11
次
|
|
|
|
|
5.
陈琦.
滑翔增程制导炮弹弹道优化及制导控制方法研究,2017
|
CSCD被引
14
次
|
|
|
|
|
6.
黄诘. 基于Radau伪谱方法的轨迹优化.
海军航空工程学院学报,2015,30(4):315-320
|
CSCD被引
4
次
|
|
|
|
|
7.
张科南. 高超声速飞行器多约束多种机动突防模式弹道规划.
弹道学报,2012,24(3):85-90
|
CSCD被引
13
次
|
|
|
|
|
8.
Boyd S.
Convex optimization,2009
|
CSCD被引
38
次
|
|
|
|
|
9.
Roh H. L1 penalized sequential convex programming for fast trajectory optimization: with application to optimal missile guidance.
International Journal of Aeronautical and Space Sciences,2020,21(2):493-503
|
CSCD被引
2
次
|
|
|
|
|
10.
Harris M W. Lossless convexification of nonconvex optimal control problems for state constrained linear systems.
Automatica,2014,50(9):2304-2311
|
CSCD被引
14
次
|
|
|
|
|
11.
陈嘉澍. 基于凸优化和切比雪夫伪谱法的再入轨迹优化.
电子技术与软件工程,2018(16):71-75
|
CSCD被引
1
次
|
|
|
|
|
12.
Acikmese B. Convex programming approach to powered descent guidance for mars landing.
Journal of Guidance,Control, and Dynamics,2007,30(5):1353-1366
|
CSCD被引
75
次
|
|
|
|
|
13.
Szmuk M. Successive convexification for 6-DoF mars rocket powered landing with free-final-time.
AIAA Guidance, Navigation, and Control Conference,2018:617-630
|
CSCD被引
1
次
|
|
|
|
|
14.
Blackmore L. Minimumlanding-error powered-descent guidance for Mars landing using convex optimization.
Journal of Guidance,Control,and Dynamics,2010,33(4):1161-1171
|
CSCD被引
34
次
|
|
|
|
|
15.
Wang J. A pseudospectral-convex optimization algorithm for rocket landing guidance.
AIAA Guidance,Navigation, and Control Conference,2018:1871-1888
|
CSCD被引
1
次
|
|
|
|
|
16.
Kwon H. A convex programming approach to mid-course trajectory optimization for air-to-ground missiles.
International Journal of Aeronautical and Space Sciences,2020,21(2):479-492
|
CSCD被引
1
次
|
|
|
|
|
17.
钱杏芳.
导弹飞行力学,2000
|
CSCD被引
313
次
|
|
|
|
|
18.
Sagliano M. Pseudospectral convex optimization for powered descent and landing.
Journal of Guidance,Control,and Dynamics,2018,41(2):320-334
|
CSCD被引
19
次
|
|
|
|
|
19.
李庆扬.
数值分析,2008
|
CSCD被引
85
次
|
|
|
|
|
20.
Garg D. Direct trajectory optimization and costate estimation of finite-horizon and infinite-horizon optimal control problems using a Radau pseudospectral method.
Computational Optimization and Applications,2011,49(2):335-358
|
CSCD被引
40
次
|
|
|
|
|
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