基于预设性能的导弹拦截鲁棒智能制导律

Translated title of the contribution: Robust Intelligent Guidance Law for Missile Interception Based on Prescribed Performance

Tian Yan, Haoyu Cheng, Mengjing Gao, Yuyan Guo, Bin Xu

Research output: Contribution to journalArticlepeer-review

Abstract

Aiming at the missile interception problem with model uncertainty,a composite learning method combined with prescribed performance control is studied. Firstly,an integrated guidance and control model for missile interception is constructed. To ensure the constraint on the miss distance between the two sides,the prescribed performance function is utilized to guarantee the tracking performance. To improve the system accuracy against the model uncertainty,a composite learning law is constructed to estimate the unknown nonlinear functions of the system online. Finally,through Lyapunov analysis,the system stability is proved. Simulation results show that the proposed algorithm can successfully intercept the target and keep the tracking error within the specified performance curve,which demonstrates the effectiveness of the algorithm.

Translated title of the contributionRobust Intelligent Guidance Law for Missile Interception Based on Prescribed Performance
Original languageChinese (Traditional)
Pages (from-to)753-761
Number of pages9
JournalYuhang Xuebao/Journal of Astronautics
Volume45
Issue number5
DOIs
StatePublished - May 2024

Fingerprint

Dive into the research topics of 'Robust Intelligent Guidance Law for Missile Interception Based on Prescribed Performance'. Together they form a unique fingerprint.

Cite this