现代防御技术 ›› 2022, Vol. 50 ›› Issue (5): 43-51.DOI: 10.3969/j.issn.1009-086x.2022.05.007

• 导航、制导与控制 • 上一篇    下一篇

拦截大机动目标的有限时间收敛制导律

吴刚1,2, 张科1   

  1. 1.西北工业大学 航天学院,陕西 西安 710072
    2.江南机电设计研究所,贵州 贵阳 550009
  • 收稿日期:2022-01-05 修回日期:2022-02-15 出版日期:2022-10-28 发布日期:2022-11-03
  • 作者简介:吴刚(1988-),男,河北张家口人。博士生,研究方向为导弹制导控制方面。

Finite Time Convergent Guidance Law for Intercepting Highly Maneuvering Targets

Gang WU1,2, Ke ZHANG1   

  1. 1.Northwestern Polytechnical University, School of Astronautics, Shaanxi Xi’an 710072, China
    2.Jiangnan Design & Research Institute of Machinery & Electricity, Guizhou Guiyang 550009, China
  • Received:2022-01-05 Revised:2022-02-15 Online:2022-10-28 Published:2022-11-03

摘要:

针对大机动目标的拦截问题,基于积分滑模控制理论提出了有限时间收敛的积分滑模制导律。采用参数自适应调节的径向基函数神经网络扰动观测器对目标机动引起的制导系统扰动进行估计,为了进一步提高估计精度,利用自适应律消除神经网络观测器的的估计误差。根据李雅普诺夫稳定性理论证明了制导律的稳定性和有限时间收敛性。通过数值仿真说明所提制导律无论是在脱靶量方面还是在弹目视线角的控制精度上都具有优异的性能。

关键词: 制导律, 积分滑模, 大机动目标, 径向基函数神经网络, 扰动观测器, 有限时间收敛

Abstract:

For intercepting highly maneuvering targets, an integral sliding mode guidance law with finite time convergence is proposed based on the integral sliding mode control theory. A radial basis function (RBF) neural network disturbance observer with adaptive parameter adjustment is used to estimate the disturbance of the guidance system caused by the target maneuver. In order to further improve the estimation accuracy, the adaptive law is used to eliminate the estimation error of the neural network observer. According to Lyapunov stability theory, the stability and finite time convergence of the guidance law are proved.The numerical simulation shows that the guidance law proposed in this paper has excellent performance both in miss distance and in the control accuracy of missile and target line of sight angle.

Key words: guidance law, integral sliding mode, highly maneuvering target, radial basis function(RBF) neural network, disturbance observer, finite time convergence

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