| MCFC燃料电池的非线性建模及基于FGA的模糊控制 |
| |
| 引用本文： | 戚志东,朱新坚,曹广益.MCFC燃料电池的非线性建模及基于FGA的模糊控制[J].上海大学学报(英文版),2006,10(2):144-150. |
| |
| 作者姓名： | 戚志东 朱新坚 曹广益 |
| |
| 作者单位： | Institute of Fuel Cell Department of Automation Shanghai Jiaotong University Shanghai 200030 P.R. China，Institute of Fuel Cell Department of Automation Shanghai Jiaotong University Shanghai 200030 P.R. China，Institute of Fuel Cell Department of Automation Shanghai Jiaotong University Shanghai 200030 P.R. China |
| |
| 基金项目： | 国家高技术研究发展计划(863计划) |
| |
| 摘 要： | 1Introduction Moltencarbonatefuelcell(MCFC)isaclearelec tricitygeneratingtechniquewithhighefficiency,which istobeusedwidely.Withoutcombustion,MCFCcon vertschemicalenergycontainedinfuelandoxidantin toelectricenergyviaelectro chemicalreaction.Per formanceof…
|
| 关 键 词： | MCFC 燃料电池 神经网络 遗传算法 非线性模型 模糊控制 |
| 文章编号： | 1007-6417（2006）02-144-07 |
| 收稿时间： | 2004-06-09 |
| 修稿时间： | 2005-04-20 |
Nonlinear modeling of molten carbonate fuel cell stack and FGA-based fuzzy control |
| |
| Zhi-dong Qi Ph. D. Candidate,Xin-jian Zhu Prof.,Guang-yi Cao.Nonlinear modeling of molten carbonate fuel cell stack and FGA-based fuzzy control[J].Journal of Shanghai University(English Edition),2006,10(2):144-150. |
| |
| Authors: | Zhi-dong Qi Ph D Candidate Xin-jian Zhu Prof Guang-yi Cao |
| |
| Institution: | Institute of Fuel Cell, Department of Automation, Shanghai Jiaotong University, Shanghai 200030, P.R. China |
| |
| Abstract: | To improve the performance of fuel cells, the operating temperature of molten carbonate fuel cell (MCFC) stack should be controlled within a specified range. In this paper, with the RBF neural network's ability of identifying complex nonlinear systems, a neural network identification model of MCFC stack is developed based on the sampled input-output data. Also, a novel online fuzzy control procedure for the temperature of MCFC stack is developed based on the fuzzy genetic algorithm (FGA). Parameters and rules of the fuzzy controller are optimized. With the neural network identification model, simulation of MCFC stack control is carried out. Validity of the model and the superior performance of the fuzzy controller are demonstrated. |
| |
| Keywords: | molten carbonate fuel cell (MCFC) neural network genetic algorithm fuzzy genetic algorithms (FGA) |
| 本文献已被 CNKI 维普 万方数据 SpringerLink 等数据库收录！ |
