中国电机工程学报2001，Vol.21Issue(1)：9-11,17,4.
基于Hopfield神经网络的线性系统参数辨识方案及在鼠笼式电机传动系统参数辨识中的应用研究
HOPFIELD NEURAL NETWORK BASED LINEAR SYSTEM PARAMETERS’ IDENTIFICATION SCHEME AND ITS APPLICATION IN ASYNCHRONOUS MOTOR DRIVE SYSTEM IDENTIFICATION
汪镭 1周国兴 1吴启迪1
作者信息
- 1. 同济大学信息与控制系，上海 200092
- 折叠
摘要
Abstract
In this paper, the Hopfield Neural Network (HNN) based linear system parameters’identification scheme is extended, and the sufficient condition for correct HNN identification is derived under the assumption that HNN inputs are the detected system state variable signal delayed by sensors. The validity of the derived identify scheme is proved by the simulation results of HNN based asynchronous motor drive system parameters' identification in consider of sensors' characteristics.关键词
Hopfield神经网络/参数辨识/鼠笼式电机传动系统Key words
HNN(hopfield neural network)/parameters ' identification/asynchronous motor drive system分类
信息技术与安全科学引用本文复制引用
汪镭,周国兴,吴启迪..基于Hopfield神经网络的线性系统参数辨识方案及在鼠笼式电机传动系统参数辨识中的应用研究[J].中国电机工程学报,2001,21(1):9-11,17,4.
