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神经模糊网络自适应模糊控制研究 被引量：2

Study on Adaptive Fuzzy Control of Neural Fuzzy Network (NFN)
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摘要 提出了一种由样品辨识、模糊推理和控制处理 3个子网模块构成的基于知识的多层神经网络 .这种网络由各子网分别构成并按照最初的模糊控制结构适当连接而建立 ,具有明确区分各组成子网功能及其知识流结构 .由于综合了模糊逻辑的推理过程及神经网络的学习能力 ,使它能够在其结构中以模糊规则的形式引入语言知识并通过网络的训练及自学习对这些知识进行加工 ,从而实现了真正意义上的自适应模糊控制器 .最后还讨论了这种 NFN is a multiplayer neural network based on knowledge, and it is composed of three modular subnets used for pattern recognition, fuzzy reasoning and control processing. A NFN combines the reasoning procedure of fuzzy logic with the learning capability of neural network. It can incorporate linguistic knowledge in the form of fuzzy rules in its structure and then process the knowledge through training and self learning of the network. The application of NFN to control of unknown nonlinear dynamic processes is discussed. A simulation result is presented to illustrate this idea.
作者 汤楠 王飞跃 Frank W.Ciarallo
机构地区 西安石油学院工业自动化系陕西西安 DepartmentofSystemsandindustrialEngineering
出处 《西安石油学院学报（自然科学版）》 2002年第1期62-65,共4页 Journal of Xi'an Petroleum Institute（Natural Science Edition)
关键词 神经模糊网络 模糊逻辑控制 自学习 自适应 模块结构 neural fuzzy network fuzzy logic control self learning
分类号 TP273.4 [自动化与计算机技术—检测技术与自动化装置]
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参考文献11

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同被引文献20

  • 1He S Z. Design of an on - line rule - adaptive fuzzy control system [ A]. IEEE Int. Conf. on Fuzzy Systems [ C]. Sam Diego,USA, 1992,83 - 91.
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  • 4Zhang Jianwei and Alois Knoll. Desiging fuzzy controllers by rapid learing. Fuzzy stes and systems, 1999,101(2)
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  • 6Zhang Jianwei and A. Knoll. Constructing fuzzy controllers with B-Spline models-principles and applications. Interational journal of intelligent systems,1997
  • 7Zhang Jianwei, K.V. Le and A. Knoll. Unsupervised learning of control spaces based on B-Spline models. Proceeding inf. IEEE international conference of fuzzy systems,1997
  • 8Zhang Jianwei, Knoll A. and K.V.Le. A new type of fuzzy logic system for adaptive modeling and control. Proceeding of the international conference on computational intelligence, Dortmund,1997, springer Verlag
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  • 10Wang Feiyin, Kim H M, Zhou M C, Dynamic backprop-agation for neuro-fuzzy networks. Proc. of int. conf. on electronics and information technology, Beijing, China,1994

引证文献2

二级引证文献6

西安石油学院学报（自然科学版）
2002年 第1期

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