Model uncertainty estimation of a solid oxide fuel cell using a Volterra-type model

被引：8

作者：

Biagiola, S. I. ^{[1
]}

Schmidt, C. ^{[1
]}

Figueroa, J. L. ^{[1
]}

机构：

[1] UNS CONICET, Inst Invest & Ingn Elect, RA-8000 Bahia Blanca, Buenos Aires, Argentina

来源：

JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS | 2014年 / 351卷 / 08期

关键词：

PREDICTIVE CONTROL; SYSTEM-IDENTIFICATION; SIMULATION; WIENER; PLANT;

D O I：

10.1016/j.jfranklin.2014.04.025

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

080201 [机械制造及其自动化];

摘要：

The dynamic nature of solid oxide fuel cells (SOFC) shows that they can be conceived as multi-input multi-output nonlinear processes. Aiming at dynamic simulation and control, this work presents a modeling study of a SOFC stack following a gray-box modeling approach. For such purpose, a Modified Generalized Memory Polynomial (MGMP) model is identified based only on input output data of the system. Additionally, dedicated estimation is dealt with in order to cope with the presence of possible model uncertainty. Simulation results are given to illustrate the quality of the obtained model which is compared with other modeling approaches. (C) 2014 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

引用

页码：4183 / 4197

页数：15

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