Context. The task of efficiency increase of power-hungry ore large crushing process by creation of optimal control system of it is<br />decided.<br />Objective is a improvement of control quality of ore large crushing process in conditions of information uncertainty about its state by<br />synthesis of optimal control based on identification of the process predictive model during control system functioning.<br />Method. It is developed the adaptive optimal control system of the ore large crushing process, which realizes the following procedures:<br />estimation of the controlled process state, its structural-parametric identification, prediction of the process progress, as well as synthesis<br />of optimal control. The solution of problem of synthesis of large crushing process optimal control is carried out during system functioning<br />by the principle of minimum of the generalized work on the sliding optimization interval with attraction of information about controlled<br />process state to the new interval of optimization and its future state by the predictive model that allows to simplify the solution of problem<br />of synthesis for nonlinear large crushing process and to compensate disturbances. The large crushing process identification is carried out by<br />definition of the operating mode and dimension of its state, based on which it is performed the model structure and parameters with the help<br />of composition of methods of global and local optimization that allows to increase the model accuracy.<br />Results. It is determined that for large crushing process the offered optimal control with prediction provides the decrease of the<br />control error in ~2 times and increase of productivity of the process of ore self-grinding, the next one in the technological line, (due to<br />stabilization of content of class +100 mm in its input ore) on 3.8%.<br />Conclusions. The scientific novelty of the work consists in development of adaptive system of large crushing process optimal control, in which the optimal control is formed in the course of functioning of control system by the principle of minimum of generalized work with the current estimation of the state of operated process and its future state by the predictive model that provides the control system invariance to the changes of operating modes of the equipment and the disturbing environment, and therefore, the improvement of control quality.<br />The practical significance of results of the work consists in development of algorithms of the current estimation and prediction of large<br />crushing process state, its identification and synthesis of optimal control realizing control system.
Науковий журнал «Радіоелектроніка, інформатика, управління»
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Korniienko, V. I.; National Mining University, Dnipro, Ukraine Matsiuk, S. M.; National Mining University, Dnipro, Ukraine Udovyk, I. M.; National Mining University, Dnipro, Ukraine |
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Context. The task of efficiency increase of power-hungry ore large crushing process by creation of optimal control system of it is<br />decided.<br />Objective is a improvement of control quality of ore large crushing process in conditions of information uncertainty about its state by<br />synthesis of optimal control based on identification of the process predictive model during control system functioning.<br />Method. It is developed the adaptive optimal control system of the ore large crushing process, which realizes the following procedures:<br />estimation of the controlled process state, its structural-parametric identification, prediction of the process progress, as well as synthesis<br />of optimal control. The solution of problem of synthesis of large crushing process optimal control is carried out during system functioning<br />by the principle of minimum of the generalized work on the sliding optimization interval with attraction of information about controlled<br />process state to the new interval of optimization and its future state by the predictive model that allows to simplify the solution of problem<br />of synthesis for nonlinear large crushing process and to compensate disturbances. The large crushing process identification is carried out by<br />definition of the operating mode and dimension of its state, based on which it is performed the model structure and parameters with the help<br />of composition of methods of global and local optimization that allows to increase the model accuracy.<br />Results. It is determined that for large crushing process the offered optimal control with prediction provides the decrease of the<br />control error in ~2 times and increase of productivity of the process of ore self-grinding, the next one in the technological line, (due to<br />stabilization of content of class +100 mm in its input ore) on 3.8%.<br />Conclusions. The scientific novelty of the work consists in development of adaptive system of large crushing process optimal control, in which the optimal control is formed in the course of functioning of control system by the principle of minimum of generalized work with the current estimation of the state of operated process and its future state by the predictive model that provides the control system invariance to the changes of operating modes of the equipment and the disturbing environment, and therefore, the improvement of control quality.<br />The practical significance of results of the work consists in development of algorithms of the current estimation and prediction of large<br />crushing process state, its identification and synthesis of optimal control realizing control system. |
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Zaporizhzhya National Technical University 2018-05-29 13:24:17 |
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application/pdf http://ric.zntu.edu.ua/article/view/132474 |
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Radio Electronics, Computer Science, Control; No 1 (2018): Radio Electronics, Computer Science, Control |
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Copyright (c) 2018 V. I. Korniienko, S. M. Matsiuk, I. M. Udovyk |
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