CLC number: TP273
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2017-10-18
Cited: 0
Clicked: 7576
Hong Song, Jia-heng Zhang, Ping Yang, Hao-cai Huang, Shu-yue Zhan, Teng-jun Liu, Yi-lu Guo, Hang-zhou Wang, Hui Huang, Quan-quan Mu, Mei-fen Fang, Ming-yuan Yang. Modeling of a dynamic dual-input dual-output fast steering mirror system[J]. Frontiers of Information Technology & Electronic Engineering, 2017, 18(10): 1488-1498.
@article{title="Modeling of a dynamic dual-input dual-output fast steering mirror system",
author="Hong Song, Jia-heng Zhang, Ping Yang, Hao-cai Huang, Shu-yue Zhan, Teng-jun Liu, Yi-lu Guo, Hang-zhou Wang, Hui Huang, Quan-quan Mu, Mei-fen Fang, Ming-yuan Yang",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="18",
number="10",
pages="1488-1498",
year="2017",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.1601221"
}
%0 Journal Article
%T Modeling of a dynamic dual-input dual-output fast steering mirror system
%A Hong Song
%A Jia-heng Zhang
%A Ping Yang
%A Hao-cai Huang
%A Shu-yue Zhan
%A Teng-jun Liu
%A Yi-lu Guo
%A Hang-zhou Wang
%A Hui Huang
%A Quan-quan Mu
%A Mei-fen Fang
%A Ming-yuan Yang
%J Frontiers of Information Technology & Electronic Engineering
%V 18
%N 10
%P 1488-1498
%@ 2095-9184
%D 2017
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.1601221
TY - JOUR
T1 - Modeling of a dynamic dual-input dual-output fast steering mirror system
A1 - Hong Song
A1 - Jia-heng Zhang
A1 - Ping Yang
A1 - Hao-cai Huang
A1 - Shu-yue Zhan
A1 - Teng-jun Liu
A1 - Yi-lu Guo
A1 - Hang-zhou Wang
A1 - Hui Huang
A1 - Quan-quan Mu
A1 - Mei-fen Fang
A1 - Ming-yuan Yang
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 18
IS - 10
SP - 1488
EP - 1498
%@ 2095-9184
Y1 - 2017
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.1601221
Abstract: A modeling method is proposed for a dynamic fast steering mirror (FSM) system with dual inputs and dual outputs. A physical model of the FSM system is derived based on first principles, describing the dynamics and coupling between the inputs and outputs of the FSM system. The physical model is then represented in a state-space form. Unknown parameters in the state-space model are identified by the subspace identification algorithm, based on the measured input-output data of the FSM system. The accuracy of the state-space model is evaluated by comparing the model estimates with measurements. The variance-accounted-for value of the state-space model is better than 97%, not only for the modeling data but also for the validation data set, indicating high accuracy of the model. Comparison is also made between the proposed dynamic model and the conventional static model, where improvement in model accuracy is clearly observed. The model identified by the proposed method can be used for optimal controller design for closed-loop FSM systems. The modeling method is also applicable to FSM systems with similar structures.
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