|Table of Contents|

Temperature Modeling Based on ANFIS and Improved Fuzzy Control of DMFC

《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

Issue:
2008年06期
Page:
749-753
Research Field:
Publishing date:

Info

Title:
Temperature Modeling Based on ANFIS and Improved Fuzzy Control of DMFC
Author(s):
QI Zhi-dong
School of Automation,NUST,Nanjing 210094,China
Keywords:
direct methanol fuel cell adaptive neural fuzzy inference system(ANFIS) fuzzy genetic algorithms(FGA)
PACS:
TM911.4
DOI:
-
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.

References:

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Memo

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Last Update: 2008-12-30