计算机应用与软件2017，Vol.34Issue(6)：236-241,6.DOI:10.3969/j.issn.1000-386x.2017.06.043
基于神经网络的非线性气动弹性系统辨识
IDENTIFICATION OF NONLINEAR AEROELASTIC SYSTEMS BASED ON NEURAL NETWORK
摘要
Abstract
Because of the nonlinearity and uncertainty of the aeroelastic system, the traditional identification method is difficult to meet in engineering.In this paper, a fuzzy wavelet neural network (FWNN) identification method is proposed.Firstly, the FWNN network is constructed by the combination of interval 2 fuzzy logic system and wavelet neural network, which can approach the nonlinear AE system with uncertainties.Then, considering the fastness and accuracy of identification, the system adopts a set of fuzzy IF-THEN rules, and a single hidden layer wavelet neural network structure is used for the fuzzy consequent parts.Parameter learning is based on the Lyapunov stability of the sliding mode learning algorithm to ensure the existence of the parameters of the system uncertainty, the identification error can be faster convergence.Finally, the simulation of the nonlinear binary wing section is carried out to verify the effectiveness of the model.关键词
系统辨识/非线性气动弹性系统/模糊小波神经网络/滑模算法Key words
System identification/Nonlinear aeroelastic system/Fuzzy wavelet neural network/Sliding mode algorithm分类
信息技术与安全科学引用本文复制引用
窦立谦,冀然..基于神经网络的非线性气动弹性系统辨识[J].计算机应用与软件,2017,34(6):236-241,6.基金项目
国家自然科学基金项目(91016018,61074064). （91016018,61074064）
