电子与控制

不确定飞行环境下的滑翔制导炮弹方案弹道优化

  • 陈琦 ,
  • 王中原 ,
  • 常思江 ,
  • 舒敬荣
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  • 1. 南京理工大学 能源与动力工程学院, 江苏 南京 210094;
    2. 陆军军官学院 二系, 安徽 合肥 230031
陈琦 男,博士研究生。主要研究方向:飞行器轨迹优化、制导与控制方法。Tel:025-84315328 E-mail:qiychan@126.com;王中原 男,博士,研究员,博士生导师。主要研究方向:飞行器飞行控制理论与技术。Tel:025-84315328 E-mail:zywang@njust.edu.cn

收稿日期: 2013-12-03

  修回日期: 2014-05-07

  网络出版日期: 2014-05-16

基金资助

国家自然科学基金(11272356);中国博士后科学基金(2013M541676)

Optimal Trajectory Design Under Uncertainty for a Gliding Guided Projectile

  • CHEN Qi ,
  • WANG Zhongyuan ,
  • CHANG Sijiang ,
  • SHU Jingrong
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  • 1. School of Energy and Power Engineering, Nanjing University of Science and Technology, Nanjing 210094, China;
    2. Department 2, Army Officer Academy, Hefei 230031, China

Received date: 2013-12-03

  Revised date: 2014-05-07

  Online published: 2014-05-16

Supported by

National Natural Science Foundation of China (11272356); China Postdoctoral Science Foundation (2013M541676)

摘要

滑翔制导炮弹因体积和成本所限存在控制能力有限的问题,有必要对其方案弹道加以合理的设计,为此提出一种不确定飞行环境下的弹道优化方法以降低方案弹道对各类随机干扰的敏感度。建立了模型偏差、滑翔启控点参数偏差、气动参数偏差及气象偏差等不确定性因素的数学模型,推导出计及随机干扰的滑翔弹动力学系统雅可比矩阵的解析表达式,利用线性协方差分析法,得到了系统误差传播方程,进而建立了不确定飞行环境下的弹道优化模型。利用Chebyshev伪谱法将弹道优化问题转换为非线性规划问题,在此基础上采用内点算法(Ipopt)获得了方案弹道的最优解。仿真结果表明,与不考虑不确定因素的设计方法相比,采用本文方法设计出的方案弹道,纵向和侧向位移散布方差明显减小,显示出对随机干扰更好的抑制效果。

本文引用格式

陈琦 , 王中原 , 常思江 , 舒敬荣 . 不确定飞行环境下的滑翔制导炮弹方案弹道优化[J]. 航空学报, 2014 , 35(9) : 2593 -2604 . DOI: 10.7527/S1000-6893.2014.0094

Abstract

Due to the limited control authority of a gliding guided projectile with tradeoffs between hardware and cost, a novel trajectory optimization method under uncertainty used to reduce the sensitivity of reference trajectories to various uncertainties is presented. The models of uncertainties that may be encountered in a real operating environment are established, and the analytic expression of the Jacobian for the glide guided projectile dynamics is derived, which can provide faster computational speeds in evaluations. The covariance propagation equation of the system is obtained by using covariance techniques, and the trajectory optimization model under uncertainties is also established. The Chebyshev pseudospectral method is implemented to transform the trajectory optimization problem into a nonlinear programming problem which is solved by an interior point filter line search algorithm package (Ipopt). The simulation results show that the proposed method has a good performance and could reduce the terminal downrange and crossrange covariance, compared with the baseline trajectory which is generated without any robustness considerations.

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