Title :
Neural-network-based model reference adaptive control
Author :
Xu Jianmin ; Zhou Qijie ; Leung, T.P.
Author_Institution :
Dept. of Autom., South China Univ. of Technol., Guangzhou, China
Abstract :
This paper presents the learning algorithm of a neural network being applied to identification of affine nonlinear systems, and proposes a neural-network-based model reference adaptive control approach. The theorems on exponential stability of the system are proven. Simulation results show that this method is feasible.<>
Keywords :
identification; learning (artificial intelligence); model reference adaptive control systems; neurocontrollers; nonlinear control systems; stability; affine nonlinear systems; exponential stability; identification; learning algorithm; neural-network-based model reference adaptive control; Adaptive control; Automation; Computer networks; Concurrent computing; Control systems; Cost function; Multi-layer neural network; Neural networks; Nonlinear dynamical systems; Nonlinear systems;
Conference_Titel :
TENCON '93. Proceedings. Computer, Communication, Control and Power Engineering.1993 IEEE Region 10 Conference on
Conference_Location :
Beijing, China
Print_ISBN :
0-7803-1233-3
DOI :
10.1109/TENCON.1993.320481
