Use of multilayer feedforward neural networks in identification and control of Wiener model

被引：42
|
作者：
AlDuwaish, H
Karim, MN
Chandrasekar, V
机构：
[1] COLORADO STATE UNIV,DEPT CHEM & BIORESOURCE ENGN,FT COLLINS,CO 80523
[2] COLORADO STATE UNIV,DEPT ELECT ENGN,FT COLLINS,CO 80523
来源：
IEE PROCEEDINGS-CONTROL THEORY AND APPLICATIONS | 1996年 / 143卷 / 03期
关键词：
neural networks; nonlinear system identification; Wiener model;
D O I：
10.1049/ip-cta:19960376
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The problem of identification and control of a Wiener model is studied. The proposed identification model uses a hybrid model consisting of a linear autoregressive moving average model in cascade with a multilayer feedforward neural network. A two-step procedure is proposed to estimate the linear and nonlinear parts separately. Control of the Wiener model can be achieved by inserting the inverse of the static nonlinearity in the appropriate loop locations. Simulation results illustrate the performance of the proposed method.
引用
收藏
页码：255 / 258
页数：4
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