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Hybrid Neuro-Fuzzy Network-Priori Knowledge Model in Temperature Control of a Gas Water Heater System
Rio de Janeiro, Brazil December 06-December 09
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICHIS.2005.60Fifth International Conference on Hyb ...
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J. A. Vieira, F. Morgado Dias, A. M. Mota, "Hybrid Neuro-Fuzzy Network-Priori Knowledge Model in Temperature Control of a Gas Water Heater System," Hybrid Intelligent Systems, International Conference on, pp. 116-124, Fifth International Conference on Hybrid Intelligent Systems (HIS'05), 2005.
 
 
BibTex
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@article{ 10.1109/ICHIS.2005.60,
author = {J. A. Vieira and F. Morgado Dias and A. M. Mota},
title = {Hybrid Neuro-Fuzzy Network-Priori Knowledge Model in Temperature Control of a Gas Water Heater System},
journal ={Hybrid Intelligent Systems, International Conference on},
volume = {0},
year = {2005},
isbn = {0-7695-2457-5},
pages = {116-124},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICHIS.2005.60},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Hybrid Intelligent Systems, International Conference on
TI - Hybrid Neuro-Fuzzy Network-Priori Knowledge Model in Temperature Control of a Gas Water Heater System
SN - 0-7695-2457-5
SP116
EP124
A1 - J. A. Vieira,
A1 - F. Morgado Dias,
A1 - A. M. Mota,
PY - 2005
KW - null
VL - 0
JA - Hybrid Intelligent Systems, International Conference on
ER -
 
J. A. Vieira, Department of Electrotecnica of the Escola Superior de Tecnologia, Portugal
F. Morgado Dias, Department of Electrotecnica of the Escola Superior de Tecnologia, Portugal
A. M. Mota, Universidade de Aveiro, Campus Santiago, Aveiro, Portugal
The Neuro-Fuzzy Hybrid Model (NFHM) of the gas water gas heater consists in a cascade connection of a neuro-fuzzy model with a first principles model. The proposed hybrid model is tuned using gradient decent combined with least square algorithm off-line. A Smith predictive controller is constructed based in the water heater hybrid model. Due to the characteristics of the model, the Smith predictive control structure is simplified, linearizing the system relatively to the input gas flow and it presents a special configuration for multiple input with different time delays. Finally, the control of the output water temperature results are shown and discussed.
Citation:
J. A. Vieira, F. Morgado Dias, A. M. Mota, "Hybrid Neuro-Fuzzy Network-Priori Knowledge Model in Temperature Control of a Gas Water Heater System," his, pp.116-124, Fifth International Conference on Hybrid Intelligent Systems (HIS'05), 2005
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