High-Power AC Servo System Identification Research Based on Wavelet Neural Network

被引：3

作者：

Hou, Runmin ^{[1
]}

Liu, Rongzhong ^{[1
]}

Hou, Yuanlong ^{[1
]}

Gao, Qiang ^{[1
]}

机构：

[1] Nanjing Univ Sci & Technol, Sch Mech Engn, Nanjing 210094, Jiangsu, Peoples R China

来源：

ADVANCES IN MANUFACTURING TECHNOLOGY, PTS 1-4 | 2012年 / 220-223卷

关键词：

Wavelet Neural Network; AC Servo System; RBF Neural Network; System Identification;

D O I：

10.4028/www.scientific.net/AMM.220-223.997

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

As a result of the non-linear characteristics and the uncertain disturbances in high-power AC servo system, it is difficult to construct an accurate mathematical model. In order to solve this problem, this article proposes a system identification method based on wavelet neural network. It makes full use of the advantages of the wavelet which combines neural network good time-frequency localization property and volatility of wavelet function and the nonlinear mapping capacity, self-learning and adaptive capacity of neural networks to solve the problem of non-unique RBF neural network approximation function expression. The simulation results show that the convergence rate, robustness and approximation accuracy of this method are better than the traditional neural network.

引用

页码：997 / 1002

页数：6