書誌事項
- タイトル別名
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- Rheology-Based Rolling Friction Modeling with Parameterization by Neural Network
- レオロジー ニ モトズク コロガリ マサツ モデリング ト ニューラル ネットワーク ニ ヨル パラメータ ドウテイ
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This paper presents novel methodologies for a rheology-based rolling friction modeling and its parameterization in ball screw-driven table systems. The rolling friction exists in the table drive mechanism as a nonlinear component, which deteriorates the control performance in the fine positioning. The rolling friction behaviors, therefore, should be clarified to provide a precise numerical simulator and to design effective compensators. In the rolling friction modeling, a rheology-based friction model is introduced, considering the characteristics of contact points at the friction surface. The proposed friction model, in addition, is formulated by a neural network (NN), where the network parameters can be identified to express the actual friction behaviors. The proposed rolling friction modeling has been evaluated by a series of numerical simulations and experiments using a prototype for industrial positioning devices.
収録刊行物
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- 精密工学会誌
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精密工学会誌 76 (7), 819-826, 2010
公益社団法人 精密工学会
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詳細情報 詳細情報について
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- CRID
- 1390282679774821888
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- NII論文ID
- 130000421876
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- NII書誌ID
- AN1003250X
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- ISSN
- 1882675X
- 09120289
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- NDL書誌ID
- 10768918
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