A Bee Colony Neuro-Fuzzy Controller to Improve Well Premixed Combustion

Abstract In order to actively control combustion reaction, this study proposes an adaptive neuro-fuzzy (ANFIS) scheme of interaction between premixed reaction and acoustic flame perturbation where the pressure movement will be considered as model perturbation. Using Cantera database, it is possible investigate mechanisms by which process interacts with acoustic, vorticity, entropy waves. A well-stirred reactor (WSR) has been extensively used processes in three different zone regimes. We designed architecture achieve intelligent representation system for various operating scenarios, was motivated complexity mathematical that being used. This goal accomplished artificial bee colony (ABC), uses simulated data from a optimize less computational expense. The optimized identifier converted neural-based controller outputs system. keeping temperature set point, results demonstrate remarkable attenuation acceptable quality (NOx emission).