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弹箭与制导学报 >

2015 , Vol. 35 >Issue 3: 19 - 22

DOI: https://doi.org/10.15892/j.cnki.djzdxb.2015.03.006

导弹与制导技术

基于 RBFNN 增益调节的自适应滑模制导律

  • 李解 ,
  • 雷虎民 ,
  • 王华吉 ,
  • 朱苏北
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  • 空军工程大学防空反导学院,西安 710051

李解(1991-),男,江苏镇江人,硕士研究生,研究方向:飞行器制导与控制。

收稿日期: 2014-05-13

  网络出版日期: 2025-05-26

基金资助

航空科学基金(20130196004)

收起

Adaptive Sliding Mode Guidance Law Based on RBFNN Gain Regulation

  • LI Jie ,
  • LEI Humin ,
  • WANG Huaji ,
  • ZHU Subei
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  • Air and Missile Defense College, Air Force Engineering University, Xi'an 710051, China

Received date: 2014-05-13

  Online published: 2025-05-26

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摘要

为提高末制导精度,设计了一种RBF滑模制导律。根据滑模变结构理论推导了一种基于零化视线角速率的滑模制导律,分析了目标机动与切换项增益的关系,利用RBF神经网络对切换项增益进行在线估计,最后将所设计的RBF滑模制导律与滑模制导律、比例导引律进行仿真对比。仿真结果表明所设计的制导律能实时调节切换项增益,有效拦截不同的机动目标,减小了脱靶量并提高了系统的鲁棒性。

关键词： 滑模制导律; RBF神经网络; 切换增益

本文引用格式

李解 , 雷虎民 , 王华吉 , 朱苏北 . 基于 RBFNN 增益调节的自适应滑模制导律[J]. 弹箭与制导学报, 2015 , 35(3) : 19 -22 . DOI: 10.15892/j.cnki.djzdxb.2015.03.006

Abstract

To improve accuracy of guidance system in terminal guidance phase, a RBF sliding mode guidance law was designed. A sliding mode guidance law based on zeroing line of sight rate was deduced with the theory of sliding mode variable structure control. With analysis of relationship between target maneuvering and switch gain, RBF neural networks were used for switch gain online regulation. Finally, compared with sliding mode guidance law and proportional navigation, the simulation results show that the RBF sliding mode guidance law has stronger robustness for target maneuvering and reduces target-missing effectively.

Key words： sliding mode guidance; RBF neural networks; switch gain

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参考文献

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