Thermal Science 2011 Volume 15, Issue 2, Pages: 321-338
Full text ( 1152 KB)
Cited by

Computationally intelligent modeling and control of fluidized bed combustion process

Ćojbašić Žarko M., Nikolić Vlastimir D., Ćirić Ivan T., Ćojbašić Ljubica R.

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

More data about this article available through SCIndeks