Title :
Self-tuning of controller using neural network and genetic algorithm
Author :
Xing, Zongyi ; Jia, Limin ; Shi, Tianyun
Author_Institution :
Res. Center For Intelligent systems, China Acad. of Railways Sci., Beijing, China
Abstract :
This paper presents a scheme of self-tuning of controllers. The proposed scheme employs neural networks to map the nonlinear relationships between parameters of controller and performance specifications of step response. Genetic algorithm is used to optimize these parameters. Self-tuning of fuzzy logic controller shows the effectiveness of the proposed scheme.
Keywords :
adaptive control; genetic algorithms; neurocontrollers; optimal control; self-adjusting systems; step response; GA; controller parameters; controller self-tuning; genetic algorithm; neural network; nonlinear relationships; step response performance specifications; Automatic control; Automation; Control systems; Fuzzy logic; Genetic algorithms; Intelligent control; Intelligent systems; Neural networks; Rail transportation;
Conference_Titel :
Intelligent Control and Automation, 2002. Proceedings of the 4th World Congress on
Print_ISBN :
0-7803-7268-9
DOI :
10.1109/WCICA.2002.1022215
