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
收藏
页码：85 / 104
页数：20
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