計測自動制御学会 部門大会/部門学術講演会資料
第2回制御部門大会
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モデル誤差の経時変化特性, 圧延条件特性の同時学習方法
山根 明仁岩本 宏之
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p. 49

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A modeling error has a time-variant factor like the influence of roll wear and a factor by rolling conditions like the size characteristic. If both factors are not distinguished when learning the modeling errors and adaptation of a setup control for the following rolling piece are executed, the appropriate compensation is not obtained, then accuracy gets wores. We propose the synchronous learning algorithm for both factors with learning gain scheduling to improve learning efficiency. Finally, the application simulation using hot-rolled width data shows that standard deviation for modeling error can be reduced 20% compared with the conventional method.

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© 2002 SICE
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