Dynamic neural network controller model of PEM fuel cell system

被引：90

作者：

Hatti, Mustapha ^{[1
]}

Tioursi, Mustapha ^{[2
]}

机构：

[1] Nucl Res Ctr Birine, Nucl Technol Div, Ain Oussera 17200, Djelfa, Algeria

[2] Univ Sci & Technol Oran, Dept Elect Engn, El Mnaouar 31000, Oran, Algeria

来源：

INTERNATIONAL JOURNAL OF HYDROGEN ENERGY | 2009年 / 34卷 / 11期

关键词：

PEM fuel cells; Dynamic neural network controller; Dynamic model; Hydrogen; POWER;

D O I：

10.1016/j.ijhydene.2008.12.094

中图分类号：

O64 [物理化学（理论化学）、化学物理学];

学科分类号：

070304 ; 081704 ;

摘要：

This paper presents the artificial intelligence techniques to control a proton exchange membrane fuel cell system process, using particularly a methodology of dynamic neural network. In this work a dynamic neural network control model is obtained by introducing a delay line in the input of the neural network. A static production system including a PEMFC is subjected to variations of active and reactive power. Therefore the goal is to make the system follow these imposed variations. The simulation requires the modelling of the principal element (PEMFC) in dynamic mode. The simulation results demonstrate that the model-based dynamic neural network control scheme is appropriate for controlling, the stability of the identification and the tracking error were analyzed, and some reasons for the usefulness of this methodology are given. (C) 2009 International Association for Hydrogen Energy. Published by Elsevier Ltd. All rights reserved.

引用

页码：5015 / 5021

页数：7

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