Title :
Neural learning control
Author :
Wang, Cong ; Hill, David J. ; Chen, Guanrong
Author_Institution :
Dept. of Electron. Eng., City Univ. of Hong Kong, China
Abstract :
This paper studies neural learning control. Based on an earlier result for deterministic learning of unknown system dynamics from a stable control process, this paper provides detailed analysis on how the learned knowledge can be effectively exploited to achieve stability and improved control performance. Comparisons on neural learning control with adaptive neural control and linear control are also included. The effectiveness of the neural learning control approach is demonstrated using simulations.
Keywords :
adaptive control; learning (artificial intelligence); learning systems; linear systems; neurocontrollers; radial basis function networks; stability; adaptive neural control; improved control performance; linear control; neural learning control; radial basis function networks; stability; stable control process; unknown system dynamics; Adaptive control; Automatic control; Control systems; Convergence; Nonlinear control systems; Performance analysis; Process control; Programmable control; Radial basis function networks; Stability analysis;
Conference_Titel :
Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on
Print_ISBN :
0-7803-8273-0
DOI :
10.1109/WCICA.2004.1342081