期刊文献+

基于一种改进自适应模糊神经技术的PEMFC系统建模和控制 被引量:6

Modeling and Novel Adaptive Fuzzy Neural Network Control of Proton Exchange Membrane Fuel Cell (PEMFC)
下载PDF
导出
摘要 从质子交换膜燃料电池(PEMFC)实际应用的角度出发,应用自适应模糊神经网络技术对PEMFC系统进行建模与控制.在建模过程中,同时应用实验数据和专家经验对模型进行辨识,使模糊节点具有明确的物理意义和初始参数的选择更加容易.在控制过程中,将训练好的网络模型作为PEMFC控制系统的参考模型,采用自适应神经网络学习算法(ANA)在线对控制器参数进行自适应调整,采用最近邻聚类算法(NCA)对控制器的模糊规则库进行更新.在仿真实验中,将自适应模糊控制算法与PID和传统模糊算法进行比较,结果表明本算法控制性能优良. From practical application, adaptive fuzzy identification and control models of proton exchange membrane fuel cell (PEMFC) were developed based on input-output sampled data and experts' experience. In the modeling process, experimental data and experts' experiences are used to identify the operating temperature of PEMFC. It makes the nodes of network possess distinct physical meanings, and chose initial value easily. In the control process, the trained network model is used as the reference model of PEMFC control system. ANA is applied to regulate parameters on-line, and NCA is applied to update the rule database of controller. At the end, the simulation and experimental results of PEMFC control system were presented, with the show of the effectiveness.
出处 《上海交通大学学报》 EI CAS CSCD 北大核心 2004年第9期1581-1586,共6页 Journal of Shanghai Jiaotong University
关键词 质子交换膜燃料电池 自适应神经模糊推理系统 自适应神经网络学习算法 最近邻聚 类算法 Adaptive control systems Computer simulation Fuzzy control Learning algorithms Neural networks Protons
  • 相关文献

参考文献9

  • 1Costamagna P, Srinivasan S. Quantum jumps in the PEMFC science and technology from the 1960s to the year 2000[J]. Power Sources, 2001, 102: 253-269.
  • 2Costamagna P. Transport phenomena in polymeric membrane fuel cell [J]. Chemical Engineering Science, 2001, 56: 323-332.
  • 3Rowe A, Li Xianguo. Mathematical modeling of proton membrane fuel cells[J]. Power Source, 2001,102: 82-96.
  • 4Lin Fa-Jeng, Wai Rong-Jong, Duan Rou-Yong.Fuzzy neural networks for identification and control of ultrasonic motor drive with LLCC resonant tech nique [J]. IEEE Trans on Industrial Electronics,1999, 46(5): 1331-1342.
  • 5Takagi T, Sugeno M. Fuzzy identification of systems and its application to modeling and control [J].IEEE Trans on Systems Man and Cybern, 1985,15(1): 116-132.
  • 6Wang L X, Mendel J M. Generating fuzzy rules by learning from examples[J]. IEEE Trans on Systems,Man, and Cybern, 1992, 22(6):1414-1427.
  • 7Wang L X, Mendel J M. Back-propagation fuzzy system as nonlinear dynamic system identifiers[A].IEEE International Conf on Fuzzy Systems[C]. San Diego:[s.n. ], 1992. 1409-1418.
  • 8Mamdani E H. An experiment in linguistic synthesis with a fuzzy logic controller[J]. Man-Machine Studies, 1975, 7: 1-13.
  • 9Wang L X. Training of fuzzy logic systems using nearest neighborhood clustering, fuzzy systems[A].Second IEEE International Conf on Fuzzy Systems [C]. San Francisco ; CA, 1993. 13-17.

共引文献1

同被引文献56

  • 1向金凤,全书海.车用25kW燃料电池冷却水系统Fuzzy-PID控制器的研究[J].华中师范大学学报(自然科学版),2004,38(2):179-182. 被引量:5
  • 2李果,毋茂盛,余达太.燃料电池输出功率的预测控制[J].电源技术,2004,28(6):348-350. 被引量:7
  • 3李湘华,肖金生,潘牧,袁润章.质子交换膜燃料电池的结构和运行参数对其性能的影响[J].武汉理工大学学报(交通科学与工程版),2006,30(6):1027-1030. 被引量:5
  • 4ROBERT J BRAUN,SANFORD A KLEIN,DOUGLAS T REINDL.Review of state-of-the-art fuel cell technologies for distributed generation-a technical and marketing analysis[R].Madison:Solar Energy Laboratory,University of Wisconsin-Madison,2000.
  • 5JAY T PUKRUSHPAN,HUEI PENG,AANNA G STEFANOPOULOU.Modeling and control of fuel cell systems and fuel processors[D].USA:University of Michigan,2003.
  • 6DUTfA S,SHIMPALEE S,VAN ZEE J W.Numerical prediction of mass-exchange between cathode and anode channels in a PEM fuel cell[J].International Journal of Heat and Mass Transfer,2001,44(1):2029-2042.
  • 7AMPHLETT J C,BAUMERT R M,HARRIS T J,et al.Performance modeling of the ballard mark Ⅳ solid polymer electrolyte fuel cell[J].J Electrochem Soc,1995,142(1):1-8.
  • 8AMPHLETT J C,BAUMERT R M,HARRIS T J,et al.Performance modeling of the ballard mark Ⅳ solid polymer electrolyte fuel cell[J].J Electrochem Soc,1995,142(1):9-15.
  • 9JAMES LARMINIE,ANDREW DICKS.Fuel cell systems explained[M].England:John Wiley,2002.
  • 10.lin J H, Yu D. Online automatic process control using observable noise factors for discrete part manu- facturing [J]. IIE Transaetlons, 2004,36 : 899 -- 911.

引证文献6

二级引证文献44

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部