@inproceedings{cb0f471adb5544239f4e50a300c465cb,
title = "Research on adaptive robust guidance law for passive homing missile against maneuvering target",
abstract = "An improved three dimensional adaptive robust guidance law is proposed for the passive homing guidance in which only line-of-sight angular rate can be measured when target maneuvered. The nonlinear control system of missile is designed according to relative motion model of missile and target, which regards coupling and target acceleration as interference. Then a sliding surface and control law is designed based on approximate parallel approaching principle and variable structure control theory. The self-learning ability of RBF neural network is used to approximate the uncertain nonlinear time-varying functions in the control law online. Finally, the network weights adaptive law is proposed according to Lyapunov theory. This method can assure the excellent adaptive ability and robustness of the system. Simulation results indicate that the guidance law is better than traditional proportional navigation and variable structure guidance law in performance.",
keywords = "adaptive, guidance law, passive homing missile, RBF neural network, sliding mode",
author = "Zhen Yang and Deyun Zhou and Qian Pan and Xiaoyang Li and Kun Zhang",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 IEEE International Conference on Information and Automation, ICIA 2017 ; Conference date: 18-07-2017 Through 20-07-2017",
year = "2017",
month = oct,
day = "20",
doi = "10.1109/ICInfA.2017.8078964",
language = "英语",
series = "2017 IEEE International Conference on Information and Automation, ICIA 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "527--530",
booktitle = "2017 IEEE International Conference on Information and Automation, ICIA 2017",
}