✦ LIBER ✦

On the design of neural-fuzzy control system

✍ Scribed by Devinder Kaur; Bin Lin

Publisher: John Wiley and Sons
Year: 1998
Tongue: English
Weight: 341 KB
Volume: 13
Category: Article
ISSN: 0884-8173
DOI: 10.1002/(sici)1098-111x(199801)13:1<11::aid-int2>3.0.co;2-#

No coin nor oath required. For personal study only.

✦ Synopsis

This article presents a neural᎐network-based fuzzy logic control NN᎐FLC system. The NN᎐FLC model has the learning capabilities for constructing membership functions and extracting fuzzy rules from training examples. Both unsupervised and supervised training algorithms are used to find the membership functions of the FLC. Competitive learning algorithms are employed to evaluate fuzzy logic rules. Matlab programs using both neural and fuzzy toolboxes are developed to implement the NN᎐FLC model. Computer simulations of the inverted pendulum controlled by NN᎐FLC system were conducted to illustrate the self-learning ability of the network.

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