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Control Systems01:10

Control Systems

1.9K
Control systems are everywhere in contemporary society, influencing diverse applications from aerospace to automated manufacturing. These systems can be found naturally within biological processes, such as blood sugar regulation and heart rate adjustment in response to stress, as well as in man-made systems like elevators and automated vehicles. A control system is essentially a network of subsystems and processes that collaboratively convert specific inputs into desired outputs.
At the heart...
1.9K
Control Systems: Applications01:25

Control Systems: Applications

1.2K
Electrical engineering plays a pivotal role in our daily lives, with control systems at the heart of many applications, from home appliances to sophisticated space shuttles. Control systems manage and regulate the behavior of devices and processes, ensuring they function safely, correctly, and efficiently.
In modern vehicles, control systems manage various functions to enhance performance and safety. The steering wheel and accelerator are primary inputs in a car's control system. The...
1.2K
Feedback control systems01:26

Feedback control systems

732
Feedback control systems are categorized in various ways based on their design, analysis, and signal types.
Linear feedback systems are theoretical models that simplify analysis and design. These systems operate under the principle that their output is directly proportional to their input within certain ranges. For instance, an amplifier in a control system behaves linearly as long as the input signal remains within a specific range. However, most physical systems exhibit inherent nonlinearity...
732
Open and closed-loop control systems01:17

Open and closed-loop control systems

1.8K
Control systems are foundational elements in automation and engineering. They are broadly categorized into open-loop and closed-loop systems. These classifications hinge on the presence or absence of feedback mechanisms, significantly influencing the system's performance, complexity, and application.
An open-loop control system operates without feedback from the output. It consists of two primary elements: the controller and the controlled process. The controller receives an input signal...
1.8K
Transfer Function in Control Systems01:21

Transfer Function in Control Systems

1.6K
The transfer function is a fundamental concept in the analysis and design of linear time-invariant (LTI) systems. It offers a concise way to understand how a system responds to different inputs in the frequency domain. It serves as a bridge between the time-domain differential equations that describe system dynamics and the frequency-domain representation that facilitates easier manipulation and analysis.
To derive the transfer function, consider a general nth-order linear time-invariant...
1.6K
Acid Attack on Concrete01:21

Acid Attack on Concrete

793
When acids come into contact with concrete, they initiate a chemical reaction that dissolves the hydrated cement paste. This process leads to softening and structural weakening of the concrete. This issue is commonly observed in environments such as chimneys, sewers, and industrial settings. The severity of the damage increases as the pH of the water interacting with the concrete drops below 6.5. In particular, a pH under 4.5 can cause significant concrete damage.
The rate at which hydrogen...
793

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Updated: Feb 15, 2026

Computerized Dynamic Posturography for Postural Control Assessment in Patients with Intermittent Claudication
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DoS攻撃下にあるマルチエージェントシステムのコンセンサス制御: ダイナミックキーベースのセキュア・スキーム

Yang Zhang, Lifeng Ma, Chen Gao

    IEEE transactions on cybernetics
    |February 13, 2026
    PubMed
    まとめ
    この要約は機械生成です。

    この研究は,サービス拒否 (DoS) 攻撃に対するディスクリートタイムマルチエージェントシステム (DTMAS) のためのセキュアでモデルフリーなコンセンサス制御方法を導入します. このアプローチは,攻撃に対する抵抗性を高め,安全な状態伝送のためにQ-ラーニング (QL) を使用しています.

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    科学分野:

    • 制御システム工学 制御システム工学
    • サイバーセキュリティー サイバーセキュリティー
    • 人工知能 (AI) とは,人工知能 (AI) のことです.

    背景:

    • ディスクリートタイムマルチエージェントシステム (DTMAS) は,サービス拒否 (DoS) 攻撃による脆弱性に直面しています.
    • セキュアな状態の送信は,サイバー脅威下でシステムの完全性を維持するために不可欠です.
    • 既存の制御方法は,洗練されたDoS攻撃に対する強度が欠如している可能性があります.

    研究 の 目的:

    • DoS攻撃下でDTMASのセキュアコンセンサス制御問題を調査する.
    • Q-learning (QL) を利用した新しいモデルフリーコントローラを提案する.
    • 通信の障害や不正アクセスへの試みにもかかわらず,堅実なコンセンサスの達成を確保する.

    主な方法:

    • QLベースのモデルフリーコントローラが開発され,制御増強マトリックスを自律的に合成します.
    • 攻撃のないシナリオで安全な状態の送信のために,ダイナミックな暗号化キー戦略が実装されています.
    • ダイナミックパラメータ拡張を伴うセーフモードは,DoS攻撃中にアクティブにされ,量子化器の飽和を防止し,部分的な通信を維持します.

    主要な成果:

    • DoS攻撃のコンセンサスを確保するための十分な条件 (頻度と持続時間) が導出されました.
    • 提案されたコントローラーは,シミュレーションで攻撃抵抗性が著しく向上したことを実証しました.
    • この方法は,量子化ベースの暗号化による状態伝送の保護に有効であることが証明されました.

    結論:

    • QL主導のモデルフリーアプローチは,DoS攻撃に直面しているDTMASで安全なコンセンサス制御のための堅牢なソリューションを提供します.
    • ダイナミックキーとセーフモードのスイッチングメカニズムは,攻撃の影響を効果的に軽減します.
    • シミュレーションの結果は,従来の技術と比較して,提案された方法の優れた性能と攻撃の回復力を検証します.