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Title: A merged-fuzzy-neural network and its application in fuzzy-neural control
Authors: 國立臺灣師範大學電機工程學系
I-H. Li
W.-Y. Wang
S.-F. Su
M.-C. Chen
Issue Date: 11-Oct-2006
Abstract: This paper proposes an observer-based adaptive fuzzy-neural controller, structured by a merged fuzzy-neural network (merged-FNN) to reduce the number of adjustable parameters. In this paper, the merged-FNN is proved to take the place of the traditional fuzzy-neural networks under some assumptions. Moreover, the overall adaptive schemes using the proposed merged-FNN guarantees that all signals involved are bounded and the output of the closed-loop system asymptotically tracks the desired output trajectory. From experimental examples, the proposed merged-FNN has far fewer parameters than the traditional FNN, and the computation time is significantly reduced. To demonstrate the effectiveness of the proposed methods, simulation results are illustrated in this paper.
Other Identifiers: ntnulib_tp_E0604_02_053
Appears in Collections:教師著作

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