DocumentCode
306922
Title
Robust direct adaptive control based on dynamic neural networks
Author
Dai, Qionghai ; Zhaongtao ; Chai, T.Y. ; Cheng, Shao
Author_Institution
Res. Center of Autom., Northeastern Univ., Liaoning, China
Volume
3
fYear
1996
fDate
11-13 Dec 1996
Firstpage
2424
Abstract
In this paper a direct adaptive control scheme for unknown affine nonlinear systems using dynamical neural networks (DNN) is presented. A stable weight learning algorithm is determined using Lyapunov theory, which is allowed to guarantee the stability of the resulting controller. The robust stability of the closed-loop system is proved
Keywords
Lyapunov methods; adaptive control; closed loop systems; neurocontrollers; nonlinear control systems; robust control; Lyapunov theory; closed-loop system; dynamic neural networks; robust direct adaptive control; stable weight learning algorithm; unknown affine nonlinear systems; Adaptive control; Automation; Convergence; Error correction; Multi-layer neural network; Neural networks; Nonlinear dynamical systems; Nonlinear systems; Robust control; Robust stability;
fLanguage
English
Publisher
ieee
Conference_Titel
Decision and Control, 1996., Proceedings of the 35th IEEE Conference on
Conference_Location
Kobe
ISSN
0191-2216
Print_ISBN
0-7803-3590-2
Type
conf
DOI
10.1109/CDC.1996.573452
Filename
573452
Link To Document