量子化下の線形システムのデータ駆動超安定化
Jared Miller1,2, Jian Zheng2, Mario Sznaier2
1J. Miller is with the Automatic Control Laboratory (IfA), Department of Information Technology and Electrical Engineering (D-ITET), ETH Zürich, Physikstrasse 3, 8092, Zürich, Switzerland.
Proceedings of the ... American Control Conference. American Control Conference
|September 2, 2025
まとめ
この研究は,定量化されたデータによる線形システムの安定化に取り組んでいます. 新しい線形プログラミングアプローチは,センサーと入力量子化にもかかわらず,システムの安定性を確保し,実例システムでの有効性を実証しています.
科学分野:
- 制御システム工学
- 情報理論
- 応用数学
背景:
- 線形システムはデータの量子化により性能が低下する可能性があります.
- 状態移行データと制御入力における定量化は,システムの安定化に重大な課題をもたらします.
- 既存の方法は,定量化下で非保守的な安定化に苦戦する.
研究 の 目的:
- 定量化状態移行データと制御入力で線形システムを安定させるための堅牢な方法を開発する.
- センサーの定量化と入力制限を考慮する非保守的なアプローチを策定する.
- 観測された量子データと一致する全てのシステムの 超安定性を確保する.
主な方法:
- セクター限定の不確実性に対する強度に基づく入力対数定量化安定化の特徴を用いる.
- 非保守的な無限次元の線形プログラムを作成します.
- この問題を2つの指数式スケーリングの 線形プログラムで解く.
主要な成果:
- 提案された方法は,量子化された線形システムに対する超安定化を成功裏に実行します.
- 無限次元の線形プログラムは 非保守的な解を提供します.
- 様々な例の量子化システムで有効性を証明した.
結論:
- 開発された線形プログラミング技術は,量子化されたシステムを安定させる強力なツールを提供します.
- このアプローチは,データの不確実性がある場合に制御システムの信頼性を高めます.
- この方法は,デジタルコンポーネントを持つシステムの堅牢な制御の分野を前進させます.
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