| Neural—networks—based Modelling and a Fuzzy Neural Networks Controller of MCFC |
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| 引用本文： | 沈承,Cao Guangyi,Zhu Xinjian.Neural—networks—based Modelling and a Fuzzy Neural Networks Controller of MCFC[J].高技术通讯(英文版),2002,8(2):76-82. |
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| 作者姓名： | 沈承 Cao Guangyi Zhu Xinjian |
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| 作者单位： | InstituteofFuelCell,DepartmentofAutomation,ShanghaiJiaotongUnivversity,Shanghai200030,P.R.China |
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| 基金项目： | 面向21世纪教育振兴行动计划(985计划) |
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| 摘 要： | Molten Carbonate Fuel Cells(MCFC) are produced with a highly efficient and clean power generation technology which will soon be widely utilized.The temperature characters of MCFC stack are briefly analyzed.A radial basis function (RBF) neural networks identification technology is applied to set up the temperature nonlinear model of MCFC stack,and the identification structure,algorithm and modeling training process are given in detail.A fuzzy controllery of MCFC stack is designed.In order to improve its online control ability,a neural network trained by the I/O data of a fuzzy controller is designed.The neural networks can memorize and expand the inference rules of the fuzzy controller and substitute for the fuzzy controller to control MCFC stack online,A detailed design of the controller is given,The validity of MCFC stack modilling based on neural networks and the superior performance of the fuzzy neural networks controller are proved by Simulations.
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| 关 键 词： | 熔化碳化燃料电池 模糊神经网控制器 神经网络 |
Neural-networks-based Modelling and a Fuzzy Neural Networks Controller of MCFC |
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| Cao Guangyi,Zhu Xinjian.Neural-networks-based Modelling and a Fuzzy Neural Networks Controller of MCFC[J].High Technology Letters,2002,8(2):76-82. |
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| Authors: | Cao Guangyi Zhu Xinjian |
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| Abstract: | Molten Carbonate Fuel Cells (MCFC) are produced with a highly efficient and clean power generation technology which will soon be widely utilized. The temperature characters of MCFC stack are briefly analyzed. A radial basis function (RBF) neural networks identification technology is applied to set up the temperature nonlinear model of MCFC stack, and the identification structure, algorithm and modeling training process are given in detail. A fuzzy controller of MCFC stack is designed. In order to improve its online control ability, a neural network trained by the I/O data of a fuzzy controller is designed. The neural networks can memorize and expand the inference rules of the fuzzy controller and substitute for the fuzzy controller to control MCFC stack online. A detailed design of the controller is given. The validity of MCFC stack modelling based on neural networks and the superior performance of the fuzzy neural networks controller are proved by Simulations. |
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| Keywords: | Molten Carbonate Fuel Cells (MCFC) Radial Basis Function (RBF) fuzzy neural networks control modelling |
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