Title :
Trajectory tracking via adaptive dynamic neural control
Author :
Sanchez, Edgar N. ; Pezez, J.P. ; Ricalde, Luis J. ; Chen, Guanrong
Author_Institution :
CINVESTAV, Unidad Guadalajara, Jalisco, Mexico
Abstract :
Presents an 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 tracking. stability of the tracking error is analyzed by means of the Lyapunov function methods. Applicability of the proposed structure is tested by simulations on two complex examples
Keywords :
Lyapunov methods; adaptive control; neurocontrollers; nonlinear control systems; recurrent neural nets; stability; tracking; uncertain systems; Lyapunov function methods; adaptive dynamic neural control; dynamic neural network; neural identifier; stability; tracking error; trajectory tracking; unknown nonlinear plants; Adaptive control; Control systems; Lyapunov method; Neural networks; Nonlinear control systems; Nonlinear dynamical systems; Nonlinear systems; Optimal control; Programmable control; Trajectory;
Conference_Titel :
Intelligent Control, 2001. (ISIC '01). Proceedings of the 2001 IEEE International Symposium on
Conference_Location :
Mexico City
Print_ISBN :
0-7803-6722-7
DOI :
10.1109/ISIC.2001.971523
