DocumentCode
490049
Title
State Feedback Stabilization of Nonlinear Systems via the Neural Network Approach
Author
Ling, Bo ; Salam, Fathi M A
Author_Institution
Circuits and Systems & Artificial Neural Nets Laboratory, Department of Electrical Engineering, Michigan State University, East Lansing, MI 48824
fYear
1993
fDate
2-4 June 1993
Firstpage
89
Lastpage
93
Abstract
We consider the state feedback stabilization of autonomous nonlinear systems described by dx/dt = Ax + Bu - f(x), where f(x) is a memoryless nonlinearity and does not necessarily satisfy the sector conditions. Classical results can not be used to infer stability of the closed loop system. By using neural network techniques, however, we find a state feedback gain matrix that ensures the asymptotic stabilit for any specified equilibrium.
Keywords
Artificial neural networks; Asymptotic stability; Bifurcation; Circuits and systems; Control theory; Hopfield neural networks; Laboratories; Neural networks; Nonlinear systems; State feedback;
fLanguage
English
Publisher
ieee
Conference_Titel
American Control Conference, 1993
Conference_Location
San Francisco, CA, USA
Print_ISBN
0-7803-0860-3
Type
conf
Filename
4792812
Link To Document