NDLI: Application of neuro-fuzzy identifier for a fossil fuel boiler system

Content Provider	IEEE Xplore Digital Library
Author	Ghezelayagh, H. Lee, K.Y.
Copyright Year	2000
Description	Author affiliation: Dept. of Electr. Eng., Pennsylvania State Univ., University Park, PA, USA (Ghezelayagh, H.)
Abstract	A multi-layer neuro-fuzzy system presents identification of a drum type boiler. This identification provides a rule-based approach to approximate the boiler dynamics from the experimental boiler data. The interconnections of neuro-fuzzy layers furnish these fuzzy rules. A genetic algorithm (GA) trains the neuro-fuzzy identifier and extracts the linguistic rules from measured boiler data. GA training takes the advantages of nonbinary alphabet and compound chromosomes to train the multi-input multi-output (MIMO) neuro-fuzzy identifier. The fuzzy membership functions need to be adjusted during the training to minimize the identifier response error. Error back-propagation training methodology is chosen to tune the membership function parameters. The identifier response is investigated in several operating points. This neuro-fuzzy identifier is implemented within an object oriented programming tool that provides portability of the identification process. Therefore, it is a strong candidate to substitute model-based identifiers in applications such as model reference control system or predictive control problem to reduce the required design time.
Starting Page	1135
Ending Page	1139
File Size	515776
Page Count	5
File Format	PDF
ISBN	0780359356
DOI	10.1109/PESW.2000.850100
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2000-01-23
Publisher Place	Singapore
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fossil fuels Boilers Object oriented modeling Predictive models Fuzzy neural networks Genetic algorithms Data mining Biological cells MIMO Object oriented programming
Content Type	Text
Resource Type	Article

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