Modeling and optimization of coal moisture control system based on BFO

Abstract

Coal moisture control process is a critical process in energy saving for pollution reduction and improving production efficiency and the quality of coke. The RBF artificial neural network approach for modeling is used to achieve precise control of coal moisture control system and against their strong coupling nonlinear systems with time-delay characteristics. The bionic BFO (Bacterial Foraging Optimization) is used to the fitness to optimize the RBF Neural network parameters. In order to achieve better results the RBF Neural network performance is optimized by these bionic BFO. This method provides a theoretical basis for accurate control of coal moisture process. The reduction of energy and pollution with improving the quality of coke is established.