基于神经网络的导弹制导控制一体化反演设计

doi:10.7527/S1000-6893.2014.0346

电子与控制

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基于神经网络的导弹制导控制一体化反演设计

周觐, 雷虎民, 李炯, 邵雷

空军工程大学防空反导学院, 西安 710051

收稿日期:2014-05-07 修回日期:2014-12-15 出版日期:2015-05-15 发布日期:2014-12-17
通讯作者: 雷虎民Tel.: 029-84789196 E-mail: hmlei@163.com E-mail:hmlei@163.com
作者简介:周觐男, 博士研究生。主要研究方向: 空天拦截器制导、控制与仿真。 Tel: 029-84789435 E-mail: zhoujindr@yahoo.com;雷虎民男, 博士, 教授, 博士生导师。主要研究方向: 飞行器导航、制导与控制。 Tel: 029-84789196 E-mail: hmlei@163.com;李炯男, 博士, 副教授, 硕士生导师。主要研究方向: 飞行器导航、制导与控制,多模复合制导。 Tel: 029-84789192 E-mail: gracefulool@163.com;邵雷男, 博士, 讲师。主要研究方向: 飞行器导航、制导与控制,多模自适应控制。 Tel: 029-84789426 E-mail: shaoleijing@126.com
基金资助:
航空科学基金 (20130196004)

Integrated missile guidance and control design based on neural network and back-stepping control theory

ZHOU Jin, LEI Humin, LI Jiong, SHAO Lei

College of Air and Missile Defense, Air Force Engineering University, Xi'an 710051, China

Received:2014-05-07 Revised:2014-12-15 Online:2015-05-15 Published:2014-12-17
Supported by:
Aeronautical Science Foundation of China (20130196004)

摘要/Abstract

摘要：

针对制导控制一体化(IGC)模型中的不确定性难以进行估计补偿的问题,提出了基于神经网络的IGC反演设计方法。首先,根据弹目相对运动关系以及导弹自动驾驶仪模型建立了三维空间中的IGC模型。其次,针对由目标机动引起的模型不确定性,提出应用高阶滑模微分器(SMD)对导弹导引头获得的弹目相对运动信息进行微分,从而估计出目标加速度的方法,然后考虑导弹自身由于参数摄动以及未建模动态引起的模型不确定性,应用SMD和神经网络模型进行在线逼近补偿,基于反演控制理论设计了带有SMD和神经网络模型的IGC算法,应用李雅普诺夫稳定性理论对所设计的控制算法进行了稳定性证明。最后,进行了导弹六自由度仿真,验证了所设计控制算法的有效性。

关键词: 制导控制一体化, 不确定性, 高阶滑模微分器, 神经网络, 反演控制

Abstract:

In allusion to the problem that the uncertainty in the integrated guidance and control (IGC) model is difficult to estimate and compensate, a novel IGC algorithm is designed based on neural network and back-stepping control theory. Firstly, the three space dimensional IGC model is constructed with the relative motion of the missile and target as well as the missile autopilot model. Secondly, aimed at the model uncertainty caused by the target maneuvers, a novel method is proposed featuring the estimation of target acceleration by introducing the high order sliding mode differentiator (SMD) which differentiates the target and missile relative motion information obtained from the missile active homing seeker. Then, the uncertainties caused by possible parameter perturbations and unmodelled dynamics are considered. With the SMD and neural network performing an online estimation and compensation, a novel IGC algorithm with SMD and neural network is designed based on the back-stepping control. The stability of the algorithm is precisely derived and analyzed. Finally, the missile's six degree of freedom simulation is carried out to verify the effectiveness of the algorithm.

Key words: integrated guidance and control, uncertainty, high order sliding mode differentiator, neural network, back-stepping control

中图分类号:

V448.2

周觐, 雷虎民, 李炯, 邵雷. 基于神经网络的导弹制导控制一体化反演设计[J]. 航空学报, 2015, 36(5): 1661-1672.

ZHOU Jin, LEI Humin, LI Jiong, SHAO Lei. Integrated missile guidance and control design based on neural network and back-stepping control theory[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2015, 36(5): 1661-1672.

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E-mail：hkxb@buaa.edu.cn

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主管单位：中国科学技术协会主办单位：中国航空学会北京航空航天大学

基于神经网络的导弹制导控制一体化反演设计

Integrated missile guidance and control design based on neural network and back-stepping control theory

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