NDLI: Dynamic Growing Interval Type-2 Fuzzy Neural Controller

Content Provider	IEEE Xplore Digital Library
Author	Fartah Tolue, S. Mohammad, R. Akbarzadeh, T. Jalaiean F, M.
Copyright Year	2013
Description	Author affiliation: Dept. of Electr. Eng., Ferdowsi Univ. of Mashhad, Mashhad, Iran (Fartah Tolue, S.; Mohammad, R.; Akbarzadeh, T.; Jalaiean F, M.)
Abstract	In this paper, a Dynamic Growing Interval Type-2 Fuzzy Neural Controller (DGIT2FNC) is proposed. This controller benefits from the advantages of self-organizing and Type-2 fuzzy systems. Using Type-2 fuzzy makes the controller capable of coping with uncertainties in rule space, uncertainties of defining the optimal rules and uncertainties generated by the lack of knowledge of pre-given parameters of the controller. This leads to better rule partitioning and consequently decreasing in number of rules. Another important merit of the proposed controller is low computational cost by applying a novel dynamic-growing mechanism in which node-pruning is omitted and instead node-adding is done more conservatively. The proposed DGIT2FNC is applied to a nonlinear system control. Performance improvement and reduction in number of rules of the DGIT2FNC are compared with a similar type-1 fuzzy controller and the merits of the proposed controller are illustrated by simulation results.
Starting Page	1
Ending Page	5
File Size	370378
Page Count	5
File Format	PDF
e-ISBN	9781479912285
DOI	10.1109/IFSC.2013.6675605
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-08-27
Publisher Place	Iran
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Type-2 Fuzzy Dynamic Growing Fuzzy Logic Controller Fuzzy neural networks (FNNs)
Content Type	Text
Resource Type	Article

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