NDLI: Generalized Tagaki-Sugeno fuzzy rules based prediction model with application to power plant pulverizing system

Content Provider	IEEE Xplore Digital Library
Author	Hui Cao Yanxia Wang Lixin Jia Gangquan Si Yanbin Zhang
Copyright Year	2013
Description	Author affiliation: State Key Lab. of Electr. Insulation & Power Equip., Xi'an Jiaotong Univ., Xi'an, China (Hui Cao; Yanxia Wang; Lixin Jia; Gangquan Si; Yanbin Zhang)
Abstract	This paper proposes a generalized Tagaki-Sugeno (TS) fuzzy rules based prediction model and apply it to estimate the pulverizing capability of ball mill pulverizing system of thermal power plant. The proposed method improves the core idea of the adaptive neuro-fuzzy inference system and does not use the neural network to interpret the model structure and the training process. Hence, the proposed model has generalization in a certain extent and could be applied efficiently on a variety of multi-variable and nonlinear dataset. For the proposed method, the Gaussian kernel fuzzy clustering algorithm is firstly used to determine the initial rules, and then the membership functions and the consequent parameters of TS fuzzy rules are tuned by the iterative optimization algorithm that minimizes the measure of the potential of data. The proposed model is performed on the field data obtained from a real thermal power plant and the experiments results verify the effectiveness of the proposed model.
Sponsorship	IEEE Control Syst. Soc.
Starting Page	7409
Ending Page	7414
File Size	1048570
Page Count	6
File Format	PDF
ISBN	9781467357142
ISSN	07431546
e-ISBN	9781467357173
DOI	10.1109/CDC.2013.6761065
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-12-10
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Equations Combustion Nickel
Content Type	Text
Resource Type	Article
Subject	Control and Optimization Control and Systems Engineering Modeling and Simulation

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