所属单位：

信息与控制工程学院

发表刊物：

Neurocomputing

关键字：

中文关键字：粒子群算法,气动力建模，英文关键字：PSO algorithm;aerodynamic modeling

摘要：

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.

备注：

孟月波

合写作者：

邹建华,甘旭升

第一作者：

赵亮,孟月波

论文类型：

期刊论文

卷号：

卷：

期号：

期：

页面范围：

页：212~221

是否译文：

否

发表时间：

2012-04-01