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COMPUTATIONALLY INTELLIGENT MODELLING AND CONTROL OF FLUIDIZED BED COMBUSTION PROCESS

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Author(s): Žarko M Ćojbašić | Vlastimir D Nikolić | Ivan T Ćirić | Ljubica R Ćojbašić

Journal: Thermal Science
ISSN 0354-9836

Volume: 15;
Issue: 2;
Start page: 321;
Date: 2011;
Original page

Keywords: computational intelligence | fluidized bed combustion | fuzzy systems | neural networks | genetic algorithms

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 modelling 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.
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