Abstract
The article discusses the problems of development of the system of adaptive predictive control of pellets heat treatment with online estimation of parameters of the process model. Due to nonstationarity in time of the process parameters caused by fluctuations of particle size distribution and fractional void of the layer, changes in the process equipment characteristics and the presence of noise in measurement channels, the existing automation systems of pellets heat treatment do not always allow to solve the problem of stabilization temperature profile in the pellets layer, as well as reduce the specific consumption of energy. To overcome these disadvantages the recursive least squares algorithm is proposed to use for estimating the parameters of process model which subsequently is the base for calculating the manipulated variable (the gas flow to the burner of the leading side of the indurating machine) with using the methods of Model Predictive Control theory that provides maintenance of a preset temperature regime of pellets indurating under conditions of uncontrolled disturbances. In accordance with the described approach it is suggested the variant of the structure of the system of adaptive predictive control of the temperature regime of pellets indurating in the separate gas-air chamber of indurating machine, and the simulation of this system was performed in Simulink package with the use of real data about the dependence of temperature in the heart of firing zone from gas consumption on the burner of leading side, which were obtained in a mode of passive experiment at the indurating machine OK-324 of JSC «Central GOK (ME)». The resulting system has demonstrated the high quality of the online estimation of parameters and sufficient convergence rate for conditions of pellets heat treatment. The obtained results allow us to recommend the developed method of formation of adaptive predictive control for automation of pellets heat treatment.
Highlights
Enrichment of iron ore in mining enterprises (ME) often ends with sintering of concentrate in sintering machines or straight grate induration machines
The structure of adaptive predictive control of the temperature regime pellets heat treatment in a certain gas-air chamber should consist of four parts: the control object with sensors, the bloc for object parameters estima tion, state observer for estimation of uncontrolled state variables and the bloc for calculating the optimal control action on the prediction horizon
For study of effectiveness of RLS algorithm for online estimation of parameters in the system of adaptive predictive control of pellets heat treatment, the model is implemented in Simulink package
Summary
Enrichment of iron ore in mining enterprises (ME) often ends with sintering of concentrate in sintering machines or straight grate induration machines (indurating furnaces). In terms of features of smelting process in blast furnace the end product of indurating furnaces — pellets — has a number of advantages compared with sinter, namely high durability during prolonged storage, transportation and transshipment, more uniform particle size distribution that provides better gas permeability of layer of charge materials in the blast-furnace and, leads to increasing the productivity of iron smelting and reduction of slag production. As the raw material for the production of pellets are often used finely powdered concentrates, whose share in the domestic ore-dressing plants are growing in recent years, due to the decrease of reserves of rich ore and increasing the share of poor kinds of ores. Straight grate induration machine (SGIM), in which the heat treatment of pellets is conducted, is the basic unit that affects to the productivity of the pelleti zing plant and quality of the finished product. Improvement of the methods and systems of control of heat treatment of pellets is one of the most promising directions of solving these tasks
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