DocumentCode :
3309055
Title :
Aerodynamic force modeling of quasi-steady stall phenomenon based on UKF-WNN
Author :
Zhao, Liang ; Liu, Xiaodong ; Lei, Jing
Author_Institution :
Eng. Coll., Air Force Eng. Univ., Xi´´an, China
fYear :
2009
fDate :
8-11 Aug. 2009
Firstpage :
213
Lastpage :
217
Abstract :
The paper proposed an algorithm which can get over the BP algorithm´s shortcomings of slow convergence speed, computation complexity and local minimum by using the UKF to estimate the parameters of WNN. Then it takes the phenomenon of aerodynamic modeling of quasi-steady stall for ATTAS aircraft as applying background and uses the algorithm of BP, EKF and UKF to train the WNN respectively. From the simulation results we can see that the UKF algorithm is faster in training speed and more accurate in prediction when compared with BP and EKF and it is competent for modeling of complex nonlinear aerodynamic phenomenon as well.
Keywords :
Kalman filters; aerodynamics; aircraft; backpropagation; computational complexity; minimisation; neural nets; nonlinear filters; parameter estimation; wavelet transforms; ATTAS aircraft; UKF-WNN; aerodynamic force modeling; backpropagation training algorithm; computation complexity; local minimum; parameter estimation; quasisteady stall phenomenon; unscented Kalman filter; wavelet neural network; Aerodynamics; Aircraft; Artificial neural networks; Convergence; Educational institutions; Land vehicles; Military computing; Neural networks; Predictive models; Road vehicles; aerodynamic force; kalman filter; neural network; wavelet;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Information Technology, 2009. ICCSIT 2009. 2nd IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-4519-6
Electronic_ISBN :
978-1-4244-4520-2
Type :
conf
DOI :
10.1109/ICCSIT.2009.5234422
Filename :
5234422
Link To Document :
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