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- W981951044 abstract "This paper presents selected aspects of application of artificial neural networks to identification and control of the cement grinding process occurring in the closed-circuit ball mill (Fig. 1) (13, 14). Cement grinding is a complicated, nonlinear, energy-consuming process. Control of the process by means of classical control systems is not effective. Therefore, nonstandard neural network algorithms combined with the inverse modeling method of Jordan and Jacon (2, 15, 18) are proposed for the purpose. The NARX neural network model (Fig. 3) is used, in addition to the expert operator knowledge developed on a basis of a number of experiments run at a domestic cement plant. Simulation runs in the Matlab/Simulink environment are directed to optimization of the network structure and selection of its adequate learning process. The obtained results enable concluding that the application of a neurocontroller to control of the grinding process can yield satisfactory process performance (4)." @default.
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- W981951044 date "2011-01-01" @default.
- W981951044 modified "2023-09-26" @default.
- W981951044 title "Pewne aspekty wykorzystania sztucznych sieci neuronowych dla identyfikacji i sterowania procesem przemiału cementu" @default.
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