Research on WNN aerodynamic modeling from flight data based on improved PSO algorithm

Authors:
Meng Yue-bo;Zou Jian-hua;Gan Xu-sheng;Zhao Liang
Affiliations:
The Systems Engineering Institute, Xi'an Jiaotong University, Shaanxi, Xi'an 710049, China and The Information and Control Engineering School, Xi'an University of Architecture and Technology, Shaa ...;The Systems Engineering Institute, Xi'an Jiaotong University, Shaanxi, Xi'an 710049, China;Engineering College, Air Force Engineering University, Shaanxi, Xi'an 710038, China;Engineering College, Air Force Engineering University, Shaanxi, Xi'an 710038, China
Venue:
Neurocomputing
Year:
2012

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Abstract

To depict the aerodynamic characteristics of flight vehicle accurately, a Wavelet Neural Network (WNN) method, based on improved Particle Swarm Optimization (IPSO) algorithm, is proposed for aerodynamic modeling from flight data. First the multi-particle information share strategy and mutation operation are introduced into Simple PSO algorithm in order to improve the modeling capability of WNN, and then according to modeling flow the aerodynamic model from flight data for flight vehicles is established by WNN based on IPSO algorithm. Simulation results show that the method proposed has a good capability with features of precision, convergence and surmounting prematurity or local optimum, and is also effective and feasible for aerodynamic modeling from flight data.