导弹与制导技术

基于 G-MPSP 算法的非线性制导律研究

  • 李新三 ,
  • 汪立新 ,
  • 丁邦平 ,
  • 闫循良 ,
  • 刘国辉 ,
  • 王明建
展开
  • 1 第二炮兵工程大学,西安710025
    2 第二炮兵工程大学士官职业技术教育学院,山东青州 262500

李新三(1982-),男,湖北广水人,讲师,博士,研究方向:飞行器制导与控制技术。

收稿日期: 2015-01-12

  网络出版日期: 2025-05-30

基金资助

国家自然科学基金(61203354)

Nonlinear Guidance Law Research Based on G-MPSP Technique

  • LI Xinsan ,
  • WANG Lixin ,
  • DING Bangping ,
  • YAN Xunliang ,
  • LIU Guohui ,
  • WANG Mingjian
Expand
  • 1 The Second Artillery Engineering University, Xi'an 710025, China
    2 College of Sergeant Occupation Technology Education, The Second Artillery Engineering University, Shandong Qingzhou 262500, China

Received date: 2015-01-12

  Online published: 2025-05-30

摘要

针对带有末端多约束的非线性制导问题,运用通用模型预测静态规划(G-MPSP)算法设计了一种快速求解连续时间系统具有终端落角约束的非线性最优制导律。该算法通过向后迭代求解小维数权矩阵微分方程对控制量进行更新,将动态优化问题转化为静态优化问题,计算效率得以提高。考虑目标以不同的方式机动,仿真结果表明,末端位移偏差小于1.0m,末端角度约束偏差可控制在0.1°范围内,该制导律能够满足脱靶量和末端角度双重要求,法向过载在整个制导过程中变化平缓。

本文引用格式

李新三 , 汪立新 , 丁邦平 , 闫循良 , 刘国辉 , 王明建 . 基于 G-MPSP 算法的非线性制导律研究[J]. 弹箭与制导学报, 2016 , 36(2) : 1 -5 . DOI: 10.15892/j.cnki.djzdxb.2016.02.001

Abstract

Generalized model predictive static programming (G-MPSP) technique was presented in this paper in continuous time framework for rapidly solving a class of nonlinear optimal control problems with hard multiple terminal constraints. A key feature of the technique is backward propagation of a small-dimensional weight matrix dynamics, using which the control history got updated. It leads to a static optimization problem and it is the reason for its high computational efficiency. Different maneuvering ground targets were considered in the simulation studies. Simulation results show that final miss distance is less than 1.0 m, terminal impact angle errors are less than 0.1°. Impact angle constraints are met in addition to achieving near zero miss distance and the variation in the lateral acceleration history is quite smooth throughout the engagement.

参考文献

[1]
BRYSON J A E, HOY C. Applied optimal control[M]. New York: John Wiley & Sons, 1975.
[2]
ROBERTS S M, SHIPMAN J S. Two-point boundary value problems:Shooting methods[M]. New York: American Elsevier Publishing Company Inc, 1972.
[3]
KIRK D E. Optimal control theory:an introduction[M]. New Jersey, USA: Prentice Hal, 1970.
[4]
BETTS J T. Practical methods for optimal control using nonlinear programming[M]. Philadelphia: Society for Industrial and Applied Mathematics, 2001: 61-425.
[5]
GONG Q, KANG W, ROSS I M. A pseudospectral method for the optimal control of constrained feedback linearizable systems[J]. IEEE Transactions on Automatic Control, 2006, 51(7): 1115-4129.
[6]
GONG Q, FAHROO F, ROSS I M. Spectral algorithm for pseudospectral methods in optimal control[J]. Journal of Guidance, Control, and Dynamics, 2008, 31(3): 460-471.
[7]
ROSSITER J A. Model based predictive control:A practical approach[R]. New York: CRC, 2003.
[8]
PADHI R, KOTHARI M. Model predictive static programming:A computationally efficient technique for suboptimal control design[J]. International Journal of Innovative Computing, Information and Control, 2009, 5(2): 399-411.
[9]
OZA H B, PADHI R. Impact-angle-constrained suboptimal model predictive static programming guidance of air-to-ground missiles[J]. Journal of Guidance, Control, and Dynamics, 2012, 35(1): 153-164.
[10]
郭鹏飞, 余浩平. 一种具有落角约束的非线性次优制导律[C]//第32届中国控制工程会议, 2013.
[11]
MAITY Arnab, OZA Harshal B, Radhakant Padhi. Generalized model predictive static programming and its application to 3D impact angle constrained guidance of air-to-surface missiles[C]// 2013 American Control Conference (ACC), 2013.
[12]
IMADO F, KURODA T, TAHK M J. A new missile guidance algorithm against a maneuvering target[C]// Proceedings of the AIAA Guidance, Navigation, and Control Conference and Exhibit, 1998.
文章导航

/