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• W2766968836 abstract "A neural tuner is considered as a tool to adjust speed PI-controller parameters. It is proposed to use it in a rolling mill control system to reject disturbances caused by the roll bite process. Such disturbances amplitude varies according to rolling metal parameters change. The experiments to reject disturbances effectively are conducted with the help of a mathematical and laboratory scale model of a rolling mill DC drive. The obtained results make it possible to conclude that the neural tuner usage allows one to decrease both the maximum speed deviation by 11% and the disturbance transient time by 35% comparing to a PI-controller with constant parameters. More effective disturbance rejection leads to reduction of scrap amount cut from each bloom." @default.
• W2766968836 created "2017-11-10" @default.
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• W2766968836 date "2017-05-01" @default.
• W2766968836 modified "2023-09-23" @default.
• W2766968836 title "Neural tuner based adaptive control system development to improve roll bite process effectiveness" @default.
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• W2766968836 doi "https://doi.org/10.1109/icieam.2017.8076302" @default.
• W2766968836 hasPublicationYear "2017" @default.
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