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A Learning Fuzzy Network and Its Applications to Inverted Pendulum System
Zheng TANG Yasuyoshi KOBAYASHI Okihiko ISHIZUKA Koichi TANNO
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences
Publication Date: 1995/06/25
Print ISSN: 0916-8508
Type of Manuscript: PAPER
Category: Systems and Control
fuzzy network, learning, fuzzy controller, back propagation,
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In this paper, we propose a learning fuzzy network (LFN) which can be used to implement most of fuzzy logic functions and is much available for hardware implementations. A learning algorithm largely borrowed from back propagation algorithm is introduced and used to train the LFN systems for several typical fuzzy logic problems. We also demonstrate the availability of the LFN hardware implementations by realizing them with CMOS current-mode circuits and the capability of the LFN systems by testing them on a benchmark problem in intelligent control-the inverted pendulum system. Simulations show that a learning fuzzy network can be realized with the proposed LFN system, learning algorithm, and hardware implementations.