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Application of grey system theory to phosphorite sinter process: From modeling to control
Author(s) -
Toktassynova Nigina,
Fourati Hassen,
Suleimenov Batyrbek
Publication year - 2021
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.2348
Subject(s) - particle swarm optimization , process (computing) , sintering , task (project management) , phosphorite , optimal control , computer science , control (management) , mathematical optimization , control theory (sociology) , process engineering , algorithm , engineering , materials science , mathematics , metallurgy , artificial intelligence , systems engineering , phosphorus , operating system
The sintering process of phosphorite ore occurs with a large amount of return caused by untimely process control. The control task of phosphorite ore sintering is to regulate the parameters of the process to obtain a high quality sinter. The parameter clearly responsible for sinter quality is the temperature in the wind box. Therefore, in order to solve the control task, it is necessary to predict the highest temperature of the charge (also known as the burn through point (BTP)). In this paper, the theory of grey systems is used as a predictive model, which makes it possible to obtain an adequate model that uses a small number of initial samples of real temperature data. Based on the grey model GMC(1,n) a new optimal model is presented, which is constructed by using optimization algorithm. Optimal model predicts the BTP, and to establish an optimal regulation, a control synthesis is carried out through an optimization of the prediction according to the “particle swarm” algorithm.