Neural-net-based direct self-tuning control of nonlinear plants

被引：28

作者：

Ahmed, MS ^{[1
]}

Anjum, MF ^{[1
]}

机构：

[1] UNIV MARYLAND,DEPT ELECT & COMP ENGN,COLLEGE PK,MD 20742

来源：

INTERNATIONAL JOURNAL OF CONTROL | 1997年 / 66卷 / 01期

关键词：

D O I：

10.1080/002071797224838

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Use of neural networks for direct self-tuning control of stochastic nonlinear plants has been proposed. The control is based upon inverse modelling of a pseudo-plant. The input to the pseudo-plant is same as the plant input while its output consists of a linear combination of the plant input and output. The controller is directly identified as a mean square optimal inverse estimator of the pseudo-plant. This approach allows the control of inverse unstable plants. Local convergence properties as well as results of simulation studies are presented.

引用

页码：85 / 104

页数：20

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