Grey Forecasting Model and Particle Swarm based Control of a Phosphorite Sinter Process
Résumé
The sintering process of phosphorite ore occurs with a large amount of return caused by untimely process control. The control task of the phosphorite ore sintering is to regulate parameters of the process to obtain a high quality sinter. The parameter clearly responsible on the sinter quality is the temperature in the wind box (called also burn through point (BTP)). Therefore, in order to solve the real time control task, it is necessary to predict the BTP. In this paper, the theory of grey systems is used as a predictive approach, which makes it possible to obtain an adequate model that has the character of "generalized energy system" and uses a small initial samples. Based on the developed optimal grey model GMC(1,n), which is constructed in real time by using real data at the beginning of the process, the temperature is well predicted at the end of the sintering process. When the temperature does not match the set value or to find out an optimal regulation, a control synthesis is carried out through an optimization of the prediction according to the "particle swarm" algorithm.