Fuzzy Model Predictive Control of Solid Oxide Fuel Cell with Zone Tracking

被引：5

作者：

Wu, Long ^{[1
]}

Wu, Xiao ^{[1
]}

Pan, Lei ^{[1
]}

Shen, Jiong ^{[1
]}

Li, Yiguo ^{[1
]}

Zhang, Junli ^{[1
]}

机构：

[1] Southeast Univ, Sch Energy & Environm, Minist Educ, Key Lab Energy Thermal Convers & Control, Nanjing 210096, Jiangsu, Peoples R China

来源：

IFAC PAPERSONLINE | 2019年 / 52卷 / 04期

基金：

中国国家自然科学基金;

关键词：

SOFC; fuzzy model predictive control; zone control; output trajectory optimization; DYNAMIC-MODEL; POWER; SYSTEMS; PLANT;

D O I：

10.1016/j.ifacol.2019.08.180

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Solid oxide fuel cell (SOFC) is of great importance to renewable energy generation system. In practice its output voltage should be held constant and fuel utilization rate should be guaranteed in a reasonable range respectively when the resistance load varies over a large area. In order to overcome the issues in practice, a fuzzy model predictive control with zone tracking for a SOFC power generation system is proposed. The nonlinearity and multivariable coupling are mitigated by fuzzy model and predictive control approaches respectively. The feedforward compensation is adopted to improve with the dynamic response. Zone control is integrated with fuzzy model predictive control for the purposes of satisfying fuel utilization within a desired range. A performance index with a weight function is developed to optimize controlled variables trajectory in the desired range so that the undulations of the controlled variables can be alleviated within the range. The advantages of the proposed method are manifested by simulations. (C) 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

引用

页码：210 / 215

页数：6

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