DocumentCode
2184663
Title
Chaos synchronization via adaptive recurrent neural control
Author
Sanchez, Edgar N. ; Perez, Jose P. ; Ricalde, Luis J. ; Chen, Guanrong
Author_Institution
CINVESTAV, Unidad Guadalajara, Jalisco, Mexico
Volume
4
fYear
2001
fDate
2001
Firstpage
3536
Abstract
This paper proposes a new adaptive control structure, based on a dynamic neural network, for trajectory tracking of unknown nonlinear plants. The main components of this structure include a neural identifier and a control law, which together guarantee the desired trajectory tracking performance. Stability of the tracking control is analyzed by using the Lyapunov function method, and the structure is tested by simulations on an example of complex dynamical systems: chaos synchronization
Keywords
Lyapunov methods; adaptive control; chaos generators; neurocontrollers; recurrent neural nets; Lyapunov function; adaptive control; chaos production; chaos synchronization; dynamic neural network; recurrent neural control; trajectory tracking; unknown nonlinear plants; Adaptive control; Analytical models; Chaos; Control system analysis; Lyapunov method; Neural networks; Programmable control; Stability analysis; System testing; Trajectory;
fLanguage
English
Publisher
ieee
Conference_Titel
Decision and Control, 2001. Proceedings of the 40th IEEE Conference on
Conference_Location
Orlando, FL
Print_ISBN
0-7803-7061-9
Type
conf
DOI
10.1109/.2001.980407
Filename
980407
Link To Document