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
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;
Conference_Titel :
Neural Networks, 1999. IJCNN '99. International Joint Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-5529-6
DOI :
10.1109/IJCNN.1999.832720
