Author/Authors
Cheng Shen، نويسنده , , Guang-Yi Cao، نويسنده , , Xin-Jian Zhu، نويسنده , , Xing-Jin Sun، نويسنده ,
DocumentNumber
1384491
Title Of Article
Nonlinear modeling and adaptive fuzzy control of MCFC stack
شماره ركورد
11455
Latin Abstract
To improve availability and performance of fuel cells, the operating temperature of molten carbonate fuel cells (MCFC) stack should be controlled within a specified range. However, the most existing models of MCFC are not ready to be applied in synthesis. In this paper, a radial basis function neural networks identification model of MCFC stack is developed based on the input–output sampled data. A novel adaptive fuzzy control procedure for the temperature of MCFC stack is also developed. The parameters of the fuzzy control system are regulated by back-propagation algorithm, and the rule database of the fuzzy system is also adaptively adjusted by the nearest-neighbor-clustering algorithm. Finally using the neural networks model of MCFC stack, the simulation results of the control algorithm are presented. The results show the effectiveness of the proposed modeling and design procedures for MCFC stack based on neural networks identification and the novel adaptive fuzzy control.
From Page
831
NaturalLanguageKeyword
modeling , fuzzy control , Molten carbonate fuel cells , radial basis function , Adaptive control
JournalTitle
Studia Iranica
To Page
839
To Page
839
Link To Document