THERMAL SCIENCE

International Scientific Journal

COMPUTATIONALLY INTELLIGENT MODELING AND CONTROL OF FLUIDIZED BED COMBUSTION PROCESS

ABSTRACT
In this paper modelling and control approaches for fluidized bed combustion process have been considered, that are based on the use of computational intelligence. Proposed adaptive neuro-fuzzy-genetic modeling and intelligent control strategies provide for efficient combining of available expert knowledge with experimental data. Firstly, based on the qualitative information on the desulphurization process, models of the SO2 emission in fluidized bed combustion have been developed, which provides for economical and efficient reduction of SO2 in FBC by estimation of optimal process parameters and by design of intelligent control systems based on defined emission models. Also, efficient fuzzy nonlinear FBC process modelling strategy by combining several linearized combustion models has been presented. Finally, fuzzy and conventional process control systems for fuel flow and primary air flow regulation based on developed models and optimized by genetic algorithms have also been developed. Obtained results indicate that computationally intelligent approach can be successfully applied for modelling and control of complex fluidized bed combustion process.
KEYWORDS
PAPER SUBMITTED: 2010-12-05
PAPER REVISED: 2010-12-15
PAPER ACCEPTED: 2011-04-17
DOI REFERENCE: https://doi.org/10.2298/TSCI101205031C
CITATION EXPORT: view in browser or download as text file
THERMAL SCIENCE YEAR 2011, VOLUME 15, ISSUE 2, PAGES [321 - 338]
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© 2020 Society of Thermal Engineers of Serbia. Published by the Vinča Institute of Nuclear Sciences, Belgrade, Serbia. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International licence