Research on Aerodynamic Modeling of Elman Neural Network Based on PSO Algorithm
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Gan Xusheng, Wang Minghua, Li Huaping
For the accurate description of aerodynamic characteristics for aircraft, an Elman Neural Network (ENN) aerodynamic modeling method, based on Particle Swarm Optimization (PSO) algorithm, is proposed. In the method, PSO algorithm is introduced to optimize the parameters of ENN. Simulation results indicate that the aerodynamic modeling method proposed can achieve the accuracy improvement compared with GD-NN, RBF-NN and GD-ENN, and can converge to a satisfactory precision by 60~120 iterations, it has been proved that the proposed method is feasible and effective for aerodynamic modeling from flight data.
Elman Neural Network, Particle Swarm Optimization, Aircraft, Aerodynamic Modeling.