書誌事項
- タイトル別名
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- Parallel Learning in Control Systems. Derivation of Multiple Eigenvalue Filter.
- セイギョケイ ノ ヘイレツ ガクシュウ ジュウコン フィルタ ノ テイアン
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This paper proposes a method that improves control performance in feedback control systems by introducing a multiple eigenvalue filter which has been deduced from parallel learning models. First, the controlled system model is copied to i (i=1, 2, …, k) systems corresponding to learning times. The actuating signal of the first model is added to the actuating signal of the second model, and then the actuating signal of the second model is added to the actuating signal of the third model. Likewise, the actuating signal of the k-1-th model is added to the actuating signal of the k-th model. Thus obtained k-th models are equivalent to the system which has a filter as a series compensator composed of the sum of i (i=0, 1, 2, …, k-1) multiple of the left side of the characteristic equation. In this paper, the sum is called a "multiple eigenvalue filter" and it is concluded that the filter is effective to eliminate control variable deviation without losing stability when disturbance is imposed.
収録刊行物
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- 日本機械学会論文集C編
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日本機械学会論文集C編 60 (571), 877-883, 1994
一般社団法人 日本機械学会
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詳細情報 詳細情報について
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- CRID
- 1390282681304883200
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- NII論文ID
- 130004230452
- 110002381402
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- NII書誌ID
- AN00187463
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- ISSN
- 18848354
- 03875024
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- NDL書誌ID
- 3858543
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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
- NDL
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- CiNii Articles
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- 抄録ライセンスフラグ
- 使用不可