拦截大机动目标的三维智能制导律设计  

Design of 3D Intelligence Guidance Law for Highly Maneuvering Target Interception

作　　者：王金强 刘玉祥 任韦[1] 刘伟[1] 廖志成 WANG Jinqiang;LIU Yuxiang;REN Wei;LIU Wei;LIAO Zhicheng(Jiangnan Institute of Mechanical and Electrical Design,Guiyang 550000 China)

机构地区：[1]江南机电设计研究所,贵阳550000

出　　处：《电光与控制》2022年第10期18-23,共6页Electronics Optics & Control

基　　金：国防科工委重点基础研究项目(2019-JCJQ-ZD-049)。

摘　　要：为解决大机动目标拦截过程中加速度信息难以预测的问题,利用自适应RBF神经网络和反步滑模控制技术提出一种新型三维智能制导律。首先,基于零化视线角速率的思想,建立了拦截机动目标的三维制导模型,并结合反步滑模算法设计了有限时间制导律;然后,将目标加速度信息视为控制系统的不确定性,采用RBF神经网络对其进行在线估计和补偿,同时设计自适应切换增益以抑制控制系统抖振;最终,基于Lyapunov直接法证明了整个闭环控制系统的稳定性,并通过对比仿真验证了所提三维制导律的有效性和优越性。To deal with the problem that it is difficult to predict acceleration information in the process of intercepting highly maneuvering target a novel 3D intelligence guidance law is proposed by using adaptive RBF neural network and backstepping sliding mode control technique.Firstly a 3D guidance model for maneuvering target interception is established based on the principle of zeroing the rate of Line-of-Sight(LOS)and a finite-time guidance law is designed by using backstepping sliding mode control algorithm.Then the target acceleration is regarded as the uncertainties of the control system which is online estimated and compensated for by using RBF neural network.Meanwhile an adaptive switching gain is designed to restrain the chattering of the control system.Finally the stability of the closed-loop control system is proved based on Lyapunov s direct method and the effectiveness and superiority of the proposed 3D guidance law are verified via comparative simulations.

关 键 词：导弹拦截 三维制导律 反步滑模 神经网络 自适应控制 

分 类 号：TJ765.3[兵器科学与技术—武器系统与运用工程]