Supervisor:
Southwest Ordnance Industry Bureau
Organizer:
Chongqing Ordnance Industry Society
Chongqing University of Technology
Chongqing University of Technology
Research on aerodynamic parameter identification technology of controlled projectile
| DOI: | 10.11809/bqzbgcxb2024.05.030 |
| Keywords: | controlled projectile arrow; parameter identification; Elman neural network; data interpolation; Matlab |
| Abstract: | Fast and accurate acquisition of aerodynamic parameters is a necessary prerequisite for precision guidance. Limited by the accuracy of model construction, the traditional aerodynamic parameter identification method is not accurate enough to identify the controlled projectile with complex forces. Aiming at the difficulty of aerodynamic parameter identification of controlled projectile, this paper introduces Elman recurrent neural network, uses Elman neural network’s powerful delay memory and nonlinear fitting ability to identify aerodynamic parameters, explores the feasibility of applying Elman neural network to aerodynamic parameter identification of controlled projectile, and compares the identification results with BP neural network. The simulation results show that Elman neural network can identify the aerodynamic parameters of gliding flight stage well, and the identification accuracy is higher than BP neural network. |
| Published: | 2024-05-31 |