Intelligent control of complex electrochemical systems with a neuro-fuzzy-genetic approach

被引：43

作者：

Melin, P ^{[1
]}

Castillo, O ^{[1
]}

机构：

[1] Tijuana Inst Technol, Dept Comp Sci, Chula Vista, CA 91909 USA

来源：

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS | 2001年 / 48卷 / 05期

关键词：

battery charging; fuzzy control; neural control; neuro-fuzzy control;

D O I：

10.1109/41.954559

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper describes different hybrid approaches for controlling the battery charging process. The hybrid approaches combine soft computing techniques to achieve the goal of controlling the temperature of the battery during the electrochemical charging process. We have reduced the time required for charging a battery with the use of fuzzy logic, neural networks, and genetic algorithms. In the neuro-fuzzy-genetic approach, neural networks are used for modeling the electrochemical process, fuzzy logic is used for controlling the process, and genetic algorithms are used to optimize the fuzzy system.

引用

页码：951 / 955

页数：5