マルチポイントマッチングを利用した水中ロボットの制御装置の新しい近似
Umesh Kumar Yadav1, V P Singh1, Luigi Fortuna2,3
1Department of Electrical Engineering, Malaviya National Institute of Technology, Jaipur, 302017, India.
Scientific reports
|August 22, 2025
まとめ
この研究では,多点マッチングとグレー・ウルフ・オプティマイゼーションを使用して,水中ロボット車両 (URV) の高級コントローラを低級モデルに近似しています. これにより,URVシステムの効率的で経済的なコントローラが得られます.
科学分野:
- ロボット
- 制御システム工学
- 最適化アルゴリズム
背景:
- 水中ロボット車両 (URV) の性能は,複雑な内部と外部ダイナミクスによって大きく影響されます.
- 有効な制御は,URVで望ましい勢いと運用効率を達成するために不可欠です.
- 高級コントローラと低級モデルの近似は,より経済的で効率的な制御ソリューションの可能性を提供します.
研究 の 目的:
- 高度な水中ロボット車両 (URV) システムのための効率的で効果的で経済的な低次元の (LO) コントローラーを開発する.
- 多点マッチング技術を使用してHO URVコントローラとLO URVコントローラを近似する.
- 灰色のオオカミ最適化アルゴリズム (GWOA) を使用してコントローラ近似を最適化します.
主な方法:
- HO URV コントローラとLO URV コントローラを拡大パラメータで近似する.
- 多点マッチングによるHOとLOコントローラ拡張パラメータ間のエラーの最小化,オブジェクト関数 (OF) として策定.
- GWOAを使用したOFの最適化,制約として安定状態マッチングとHurwitz安定性基準に従います.
主要な成果:
- 提案されたマルチポイントマッチングアプローチにより,LO URVモデルが成功しました.
- 既存のLO URVモデルとの比較による検証により,提案されたメソッドの有効性が示されました.
- 性能評価は,応答分析と性能エラー値 (PEV) に関する統計データによって裏付けられた LO コントローラーの適用性を示した.
結論:
- 提示された方法は,高階 URV コントローラを低階モデルに効果的に近似します.
- マルチポイントマッチングとGWOAの統合は,URVの効率的で安定した制御戦略を提供します.
- 開発されたLOコントローラは,URVアプリケーションのための実用的で経済的なソリューションを提供します.
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