Intelligent control of complex electrochemical systems with aneuro-fuzzy-genetic approach
Melin, P.
Castillo, O.
Dept. of Comput. Sci, Tijuana Inst. of Technol., Chula Vista, CA;
This paper appears in: Industrial Electronics, IEEE Transactions on
Publication Date: Oct 2001
Volume: 48,
Issue: 5
On page(s): 951-955
ISSN: 0278-0046
References Cited: 15
CODEN: ITIED6
INSPEC Accession Number: 7070155
Digital Object Identifier: 10.1109/41.954559
Current Version Published: 2002-08-07
Abstract
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
Index
Terms
Available to subscribers and IEEE members.
References
Available to subscribers and IEEE members.
Citing Documents
Available to subscribers and IEEE members.
Cart
