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Neural Model Extraction for Model-Based Control of a Neural Network Forward Model
http://hdl.handle.net/10228/00008683
http://hdl.handle.net/10228/00008683d7fcccb7-8a56-4f6d-aa34-a9a7a886183a
名前 / ファイル | ライセンス | アクション |
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neuro_17.pdf (869.6 kB)
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Item type | 学術雑誌論文 = Journal Article(1) | |||||||||||
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公開日 | 2022-01-24 | |||||||||||
資源タイプ | ||||||||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||||||||
資源タイプ | journal article | |||||||||||
タイトル | ||||||||||||
タイトル | Neural Model Extraction for Model-Based Control of a Neural Network Forward Model | |||||||||||
言語 | ||||||||||||
言語 | eng | |||||||||||
著者 |
池本, 周平
× 池本, 周平
WEKO
30354
× Takahara, Kazuma× Kumi, Taiki× Hosoda, Koh |
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抄録 | ||||||||||||
内容記述タイプ | Abstract | |||||||||||
内容記述 | Neural networks have been widely used to model nonlinear systems that are difficult to formulate. Thus far, because neural networks are a radically different approach to mathematical modeling, control theory has not been applied to them, even if they approximate the nonlinear state equation of a control object. In this research, we propose a new approach—i.e., neural model extraction, that enables model-based control for a feed-forward neural network trained for a nonlinear state equation. Specifically, we propose a method for extracting the linear state equations that are equivalent to the neural network corresponding to given input vectors. We conducted simple simulations of a two degrees-of-freedom planar manipulator to verify how the proposed method enables model-based control on neural network forward models. Through simulations, where different settings of the manipulator’s state observation are assumed, we successfully confirm the validity of the proposed method. | |||||||||||
書誌情報 |
SN Computer Science 巻 2, p. 54-1-54-14, 発行日 2021-01-23 |
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出版社 | ||||||||||||
出版者 | Springer | |||||||||||
DOI | ||||||||||||
関連タイプ | isVersionOf | |||||||||||
識別子タイプ | DOI | |||||||||||
関連識別子 | https://doi.org/10.1007/s42979-021-00456-4 | |||||||||||
日本十進分類法 | ||||||||||||
主題Scheme | NDC | |||||||||||
主題 | 501 | |||||||||||
ISSN | ||||||||||||
収録物識別子タイプ | ISSN | |||||||||||
収録物識別子 | 2661-8907 | |||||||||||
著作権関連情報 | ||||||||||||
権利情報 | Copyright (c) The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. part of Springer Nature 2021 | |||||||||||
キーワード | ||||||||||||
主題Scheme | Other | |||||||||||
主題 | Neural network | |||||||||||
キーワード | ||||||||||||
主題Scheme | Other | |||||||||||
主題 | Model based control | |||||||||||
出版タイプ | ||||||||||||
出版タイプ | AM | |||||||||||
出版タイプResource | http://purl.org/coar/version/c_ab4af688f83e57aa | |||||||||||
査読の有無 | ||||||||||||
値 | yes | |||||||||||
研究者情報 | ||||||||||||
https://hyokadb02.jimu.kyutech.ac.jp/html/100001226_ja.html | ||||||||||||
論文ID(連携) | ||||||||||||
10362487 | ||||||||||||
連携ID | ||||||||||||
8615 | ||||||||||||
資料タイプ | ||||||||||||
内容記述タイプ | Other | |||||||||||
内容記述 | Journal Article | |||||||||||
著者所属 | ||||||||||||
Kyushu Institute of Technology | ||||||||||||
著者所属 | ||||||||||||
Osaka University | ||||||||||||
著者所属 | ||||||||||||
Osaka University | ||||||||||||
著者所属 | ||||||||||||
Osaka University |