An on-line learning algorithm of parallel mode for MLPN models

被引：0
|
作者：
Yu, D. L. [1 ]
Chang, T. K. [1 ]
Yu, D. W. [2 ]
机构：
[1] Liverpool John Moores Univ, Control Syst Res Grp, Liverpool L3 5UX, Merseyside, England
[2] Northeast Univ Qinhuangdao, Dept Automat, Qinhuangdao, Peoples R China
来源：
ADVANCES IN NEURAL NETWORKS - ISNN 2007, PT 2, PROCEEDINGS | 2007年 / 4492卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
An on-line learning algorithm in parallel mode for multi-layer perceptron network (MLPN) model is proposed. The MLPN is on-line trained directly in a parallel mode. The on-line learning algorithm is based on the Extended Kalman Filter (EKF) algorithm. This network is able to learn the nonlinear dynamic behaviour of unknown time-varying systems and perform multistep-ahead prediction for control purpose. The performance of this model is evaluated in modelling a multi-variable non-linear continuous stirred tank reactor (CSTR).
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页码：432 / +
页数：2
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