@inproceedings{cee65e84d0da422abc61f81c5dbd236e,
title = "Design of BP neural network controller for infrared seeker servo system based on stribeck friction model",
abstract = "The high precision of the seeker is the key to reduce the Miss-Distance and improve precision in the guidance system of missile, and the seeker stabilized platform servo system is safeguard of the overall performance of seeker. So based on the Stribeck friction model, this paper studies and compares the precision of position and velocity that controlled by PID control and BP neural network when the seeker platform working at low speed. Finally, according to the MATLAB simulation results, applying modern control theory as controller based on Stribeck friction model can improve precision and the problem of flat and dead zone at low speed.",
keywords = "BP neural networks, PID controller, Seeker, Servo system, Stribeck friction model",
author = "Yan, {Xin Ying} and Bo Mo and Ying He",
year = "2014",
doi = "10.4028/www.scientific.net/AMM.615.409",
language = "English",
isbn = "9783038351993",
series = "Applied Mechanics and Materials",
publisher = "Trans Tech Publications Ltd.",
pages = "409--414",
booktitle = "Automatic Control and Mechatronic Engineering III",
address = "Switzerland",
note = "3rd International Conference on Automatic Control and Mechatronic Engineering, ICACME 2014 ; Conference date: 13-06-2014 Through 14-06-2014",
}