[1]戚志东.基于ANFIS的DMFC温度建模和改进模糊控制[J].南京理工大学学报(自然科学版),2008,(06):749-753.
 QI Zhi-dong.Temperature Modeling Based on ANFIS and Improved Fuzzy Control of DMFC[J].Journal of Nanjing University of Science and Technology,2008,(06):749-753.
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基于ANFIS的DMFC温度建模和改进模糊控制
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《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

卷:
期数:
2008年06期
页码:
749-753
栏目:
出版日期:
2008-12-30

文章信息/Info

Title:
Temperature Modeling Based on ANFIS and Improved Fuzzy Control of DMFC
作者:
戚志东;
南京理工大学自动化学院,江苏南京210094
Author(s):
QI Zhi-dong
School of Automation,NUST,Nanjing 210094,China
关键词:
直接甲醇燃料电池 自适应神经模糊推理系统 模糊遗传算法
Keywords:
direct methanol fuel cell adaptive neural fuzzy inference system(ANFIS) fuzzy genetic algorithms(FGA)
分类号:
TM911.4
摘要:
针对直接甲醇燃料电池(DMFC)的实时控制要求,采用自适应神经模糊推理系统(AN-FIS)对DMFC系统的工作温度进行建模与控制。基于实验数据建立DMFC电堆温度模型,避免了DMFC电堆的内部复杂性分析。以训练好的网络模型作为DMFC控制系统的参考模型,采用一种改进的模糊遗传算法(FGA)在线对神经模糊控制器的参数和模糊规则进行自适应调整。将所提出的算法与非线性PID和传统模糊算法进行实验比较,结果表明所设计的神经模糊控制器具有较好的性能。
Abstract:
To improve the performance of direct methanol fuel cell(DMFC),an adaptive neural fuzzy inference technology is adopted in the modeling and control of DMFC temperature system.In the modeling process,an ANFIS identification model of DMFC stack temperature is developed based on the input-output sampled data,which avoids the internal complexity of DMFC stack.In the controlling process,with the network model trained well as the reference model of the control system of DMFC stack,a novel fuzzy genetic algorithm(FGA) is used to regulate the parameters and fuzzy rules of a neural fuzzy controller.In the simulation,compared with the nonlinear proportional integral derivative(PID) and traditional fuzzy algorithms,the neural fuzzy controller designed in this paper gets better performance,as demonstrated by the simulation results.

参考文献/References:

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备注/Memo

备注/Memo:
基金项目:国家“863”计划(2002AA517020)  作者简介:戚志东(1976 - ) ,男,江苏盐城人,讲师,博士,主要研究方向:模糊控制、遗传算法和智能控制在燃料 电池控制中的应用, E_mail: qizhidong@sina. com. cn。
更新日期/Last Update: 2008-12-30