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First International Workshop on Knowledge Discovery and Data Mining (WKDD 2008)
A Fast and Optimal Method Based on Fuzzy Neural Networks for SINS Initial Alignment
Adelaide, Australia
January 23-January 24
ISBN: 0-7695-3090-7
ASCII Text
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Xu Bo, Sun Feng, Yu Fei, Liu Fuqiang, "A Fast and Optimal Method Based on Fuzzy Neural Networks for SINS Initial Alignment," International Workshop on Knowledge Discovery and Data Mining, pp. 601-606, First International Workshop on Knowledge Discovery and Data Mining (WKDD 2008), 2008.
 
 
BibTex
x
 
@article{ 10.1109/WKDD.2008.121,
author = {Xu Bo and Sun Feng and Yu Fei and Liu Fuqiang},
title = {A Fast and Optimal Method Based on Fuzzy Neural Networks for SINS Initial Alignment},
journal ={International Workshop on Knowledge Discovery and Data Mining},
volume = {0},
year = {2008},
isbn = {0-7695-3090-7},
pages = {601-606},
doi = {http://doi.ieeecomputersociety.org/10.1109/WKDD.2008.121},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - International Workshop on Knowledge Discovery and Data Mining
TI - A Fast and Optimal Method Based on Fuzzy Neural Networks for SINS Initial Alignment
SN - 0-7695-3090-7
SP601
EP606
A1 - Xu Bo,
A1 - Sun Feng,
A1 - Yu Fei,
A1 - Liu Fuqiang,
PY - 2008
VL - 0
JA - International Workshop on Knowledge Discovery and Data Mining
ER -
 
The paper presents an approach which applies LQ optimal control in Strap-down Inertial Navigation System (SINS) initial alignment. The detailed analysis process about this method has been shown, and anti-jamming designs were done for the approximate step-wise disturbance which appeared in the system, to gain the optimal control parameter, the fuzzy neural network is used in the method. Simulations are performed to validate the scheme for initial alignment, obtained the same precision to other alignment method. And the most splendid was that the using of the LQ optimal control reduces the alignment time consumedly, much more quickly than other traditional method. What is discovered in the simulation is while the initial error angles were smaller than 10 rees; error angle will converge to quite good cision in several seconds.
Citation:
Xu Bo, Sun Feng, Yu Fei, Liu Fuqiang, "A Fast and Optimal Method Based on Fuzzy Neural Networks for SINS Initial Alignment," wkdd, pp.601-606, First International Workshop on Knowledge Discovery and Data Mining (WKDD 2008), 2008
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