DocumentCode
1844569
Title
Design of neural stabilizing controller for nonlinear systems via Lyapunov´s direct method
Author
Shimizu, Kiyotaka ; Ito, Kazuyuki
Author_Institution
Fac. of Sci. & Technol., Keio Univ., Yokohama, Japan
Volume
3
fYear
1999
fDate
1999
Firstpage
2146
Abstract
This paper deals with a neural stabilizing controller of general nonlinear systems. The stabilizing state feedback control law is approximated with a multilayer neural network. Connection weights in the neural controller are determined by a min-max algorithm such that the Lyapunov stability theorem holds via a control Lyapunov function
Keywords
Lyapunov methods; asymptotic stability; control system synthesis; feedforward neural nets; minimax techniques; neurocontrollers; nonlinear systems; robust control; state feedback; Lyapunov function; asymptotic stability; connection weights; min-max algorithm; multilayer neural network; neurocontrol; nonlinear systems; stabilizing control; state feedback; Control systems; Indium tin oxide; Linear systems; Lyapunov method; Multi-layer neural network; Neural networks; Nonlinear control systems; Nonlinear systems; Stability analysis; State feedback;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1999. IJCNN '99. International Joint Conference on
Conference_Location
Washington, DC
ISSN
1098-7576
Print_ISBN
0-7803-5529-6
Type
conf
DOI
10.1109/IJCNN.1999.832720
Filename
832720
Link To Document