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 :
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