Title :
Identification and control of nonlinear systems using dynamic neural networks
Author :
Ren, X.M. ; Rad, A.B. ; Chan, P.T.
Author_Institution :
Dept. of Electr. Eng., Hong Kong Polytech. Univ., Kowloon, China
Abstract :
In this paper, the adaptive identification and control for continuous-time nonlinear systems are addressed using dynamic neural networks. The control scheme includes two parts: a dynamic neural network is employed to perform system identification, and then a controller based on a dynamic neural network model is developed to track a reference trajectory. Stability analysis for the identification and tracking errors is performed. Finally, the paper illustrates the effectiveness of these methods by simulations of the Duffing chaotic system and the one-link rigid robot manipulator.
Keywords :
adaptive control; chaos; continuous time systems; identification; manipulators; neurocontrollers; nonlinear control systems; stability; Duffing chaotic system; adaptive control; adaptive identification; continuous-time nonlinear systems; dynamic neural networks; one-link rigid robot manipulator; reference trajectory tracking; simulations; stability; tracking errors; Adaptive control; Control systems; Neural networks; Nonlinear control systems; Nonlinear dynamical systems; Nonlinear systems; Programmable control; Stability analysis; System identification; Trajectory;
Conference_Titel :
Intelligent Control and Automation, 2002. Proceedings of the 4th World Congress on
Print_ISBN :
0-7803-7268-9
DOI :
10.1109/WCICA.2002.1021436