書誌事項
- タイトル別名
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- Data-Driven Generalized Minimum Variance Control with Autoencoder based Dimensionality Reduction of Input Signals
抄録
<p>This paper considers data-driven type generalized minimum variance control (GMVC) for p-inputs/q-outputs (p > q) multivariable systems with static nonlinearity. In the proposed approach, an autoencoder, which can extract the feature of input data, is used. First, an encoder converts input data with p dimensions into that with q dimensions. Then, a GMV controller is designed by using the dimension-reduced input data. Finally, the nonlinearity of a plant is compensated by a decoder, which reconstructs the input data with p dimensions. The effectiveness of the presented approach is evaluated using a numerical example.</p>
収録刊行物
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- 電気学会論文誌C(電子・情報・システム部門誌)
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電気学会論文誌C(電子・情報・システム部門誌) 143 (3), 305-311, 2023-03-01
一般社団法人 電気学会
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詳細情報 詳細情報について
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- CRID
- 1390576745204768256
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- ISSN
- 13488155
- 03854221
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- 本文言語コード
- ja
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- データソース種別
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- JaLC
- Crossref
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- 抄録ライセンスフラグ
- 使用不可