| 基于RBF神经网络辨识的直接甲醇燃料电池电堆非成性建模与自适应模糊控制 |
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| 引用本文： | 苗青,曹广益,朱新坚.基于RBF神经网络辨识的直接甲醇燃料电池电堆非成性建模与自适应模糊控制[J].上海大学学报(英文版),2006,10(4):346-351. |
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| 作者姓名： | 苗青 曹广益 朱新坚 |
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| 作者单位： | 上海交通大学 |
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| 基金项目： | 国家高技术研究发展计划(863计划) |
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| 摘 要： | 1 Introduction Direct methanol fuel cell ( DMFC) is desirable toserve as the power systemfor portable devices such ascellular phones , portable computers ,etc. due to thetheoretically high energy density and the liquid fuelused that can be stored and tran…
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| 关 键 词： | DMFC 燃料电池 RBF 神经网络 控制器 |
| 文章编号： | 1007-6417（2006）04-0346-06 |
| 收稿时间： | 2004-10-29 |
| 修稿时间： | 2004-12-27 |
Nonlinear modeling based on RBF neural networks identification and adaptive fuzzy control of DMFC stack |
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| Qing Miao Ph. D. Candidate,Guang-yi Cao Ph. D.,Xin-jian Zhu.Nonlinear modeling based on RBF neural networks identification and adaptive fuzzy control of DMFC stack[J].Journal of Shanghai University(English Edition),2006,10(4):346-351. |
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| Authors: | Qing Miao Ph D Candidate Guang-yi Cao Ph D Xin-jian Zhu |
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| Institution: | (1) Fuel Cell Institute, Shanghai Jiaotong University, 200030 Shanghai, P.R. China |
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| Abstract: | The temperature models of anode and cathode of direct methanol fuel cell (DMFC) stack were established by using radial basis function (RBF) neural networks identification technique to deal with the modeling and control problem of DMFC stack. An adaptive fuzzy neural networks temperature controller was designed based on the identification models established, and parameters of the controller were regulated by novel back propagation (BP) algorithm. Simulation results show that the RBF neural networks identification modeling method is correct, effective and the models established have good accuracy. Moreover, performance of the adaptive fuzzy neural networks temperature controller designed is superior. |
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| Keywords: | direct methanol fuel cell (DMFC) stack radial basis function (RBF) neural networks controller |
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