Implementation of GA-trained GRNN for Intelligent Fast Charger for Ni-Cd Batteries

Author

Petchjatuporn, Panom ; Khaehintung, Noppadol ; Sunat, Khamron ; Sirisuk, Phaophak ; Kiranon, Wiwat

Author_Institution

Dept. of Control & Instrum. Eng., Mahanakorn Univ. of Technol., Bangkok

Volume

1

fYear

2006

fDate

14-16 Aug. 2006

Firstpage

1

Lastpage

5

Abstract

This paper presents the development of an intelligent genetic algorithm (GA) technique for training of a generalized regression neural network (GRNN) controller to achieve a compact network and to decrease battery charging time on a cost-effective RISC microcontroller. The suitable input-output data were selected from GA mechanism to establish GRNN. The computational complexity of GRNN can be reduced replaced by some simple polynomial forms. As a consequence, the fast charging device for nickel-cadmium (Ni-Cd) batteries can be efficiently implemented on a low-cost 16F876A RISC microcontroller. Experimental results are shown to demonstrate superiority of the proposed system

Keywords

battery chargers; computational complexity; generalisation (artificial intelligence); genetic algorithms; microcomputer applications; neural nets; polynomials; radial basis function networks; secondary cells; 16F876A RISC microcontroller; GA technique; Ni-Cd; battery charging time; computational complexity; generalized regression neural network controller; intelligent fast charger; intelligent genetic algorithm; nickel-cadmium batteries; polynomial forms; radial basis functions; Batteries; Control systems; Genetic algorithms; Genetic engineering; Intelligent networks; Microcontrollers; Neural networks; Reduced instruction set computing; Telecommunication control; Temperature; RISC microcontroller; fast charging; genetic algorithm; radial basis functions; the generalized regression neural network;

fLanguage

English

Publisher

ieee

Conference_Titel

Power Electronics and Motion Control Conference, 2006. IPEMC 2006. CES/IEEE 5th International

Conference_Location

Shanghai

Print_ISBN

1-4244-0448-7

Type

conf

DOI

10.1109/IPEMC.2006.4777963

Filename

4777963