Wavelet Neural Network Based on SSUKF and Its Applications in Aerodynamic Force Modeling for Flight Vehicle

摘要：

To overcome the shortcomings of traditional Wavelet Neural Network (WNN), a WNN algorithm based on modified Unscented Kalman Filter (UKF) is proposed.The algorithm uses a UKF based on Spherical Simplex sigma-point (SSUKF) to estimate the WNN parameters, which can improve the learning capability of WNN. The aerodynamic force modeling experiment for flight vehicle indicate that, compared with BP, EKF and UKF, SSUKF for the WNN training has a better ability with features of convergence, precision and calculation, and is also a good method for aerodynamic force modeling for flight vehicle.

关键词： Unscented Transformation Kalman Filter Wavelet Neural Network Aerodynamic Force

作者: Gan Xusheng Duanmu Jingshun Cong Wei

作者单位: XiJing College, Xian, Shaanxi, 710123, China Engineering College, Air Force Engineering University, Xian, Shaanxi, 710038, China

会议类型: 国际会议

会议名称: 2010 International Conference on Measuring Technology and Mechatronics Automation(ICMTMA 2010)(2010年检测技术与机电自动化国际会议)

会议地点: 长沙

会议语种:英文

页码: 3341-3344

在线出版日期: 2010-03-13（万方平台首次上网日期，不代表论文的发表时间）