不確実な条件下での内/外力の追跡のための2段階の可変阻力制御
PubMedで要約を見る
まとめ
この要約は機械生成です。この研究は,双腕マニピュレータのための2段階の適応変数インペダンス制御を提示し,力追跡とシステムの安定性を改善します. 新しいフォース・フィードバック・可変インペダンス・コントローラ (FFVIC) は,複雑な環境における従来の方法の性能を上回ります.
科学分野
- ロボットと制御システム
- メカトロニクス
- 人工知能
背景
- 協調した双腕操作は高度なロボットアプリケーションに不可欠ですが,乱れやシステムの不確実性のために正確な力制御は依然として困難です.
- 既存の制御方法は,複雑な協力的なタスクの際に,内部と外部の力規制と闘っています.
研究 の 目的
- 双腕マニピュレーターの内部と外部の精密なフォース追跡のための堅牢な2レベル適応変阻力制御システムを開発し,検証する.
- 不確実な環境での操作器の柔軟性,適合性,および干渉拒否能力を強化する.
主な方法
- 2階の適応変数インペダンス制御アーキテクチャの実装
- オブジェクトレベルのハイブリッドインピデンスコントローラーの設計.
- マニピュレータレベルのフォース・フィードバック可変阻抗コントローラ (FFVIC) の開発
主要な成果
- 提案された制御スキームは,ダブルアームマニピュレーターシステムにおける内部と外部の両方の力をうまく制御した.
- 実験的な検証により,FFVICのフォース・トラッキング性能は従来のインペダンス・コントローラよりも優れていることが示された.
- 理論的分析は,ルースの安定性基準を用いてシステムのアシンプトティックな安定性を確認した.
結論
- 2階の適応変数インペダンス制御システムは,双腕マニピュレーターの調整操作における課題を効果的に解決します.
- FFVICは強化されたフォーストラッキング機能を備えており,高い精度と適応性を要求するタスクに適しています.
- この研究は,実際の協働ロボットシナリオにおける 提案されたメソッドの優越性と強さを検証しています.
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