DocumentCode
1424072
Title
Control of perturbed systems using neural networks
Author
Lin, Chun-Liang
Author_Institution
Dept. of Autom. Control Eng., Feng Chia Univ., Taichung, Taiwan
Volume
9
Issue
5
fYear
1998
fDate
9/1/1998 12:00:00 AM
Firstpage
1046
Lastpage
1050
Abstract
Stability conditions for a perturbed plant control by a conventional robust controller and a neurocontroller are presented. The neural net-based direct inverse controller is proposed to aid the robust controller to further suppress the output error resulting from the unmodeled residuals. A procedure for determining the permissible network´s output under which the overall closed-loop system will be robustly stable is provided
Keywords
closed loop systems; neurocontrollers; perturbation techniques; robust control; stability criteria; closed-loop system; direct inverse controller; neural networks; neurocontroller; output error suppression; perturbed plant control; perturbed system control; robust controller; stability conditions; unmodeled residuals; Control systems; Error correction; Flexible structures; Neural networks; Riccati equations; Robust control; Robust stability; Robustness; Uncertainty; Upper bound;
fLanguage
English
Journal_Title
Neural Networks, IEEE Transactions on
Publisher
ieee
ISSN
1045-9227
Type
jour
DOI
10.1109/72.712189
Filename
712189
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