Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Control Systems01:10

Control Systems

1.8K
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...
1.8K
Control Systems: Applications01:25

Control Systems: Applications

1.1K
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...
1.1K
Feedback control systems01:26

Feedback control systems

694
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...
694
Open and closed-loop control systems01:17

Open and closed-loop control systems

1.6K
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...
1.6K
Transfer Function in Control Systems01:21

Transfer Function in Control Systems

1.5K
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...
1.5K
Nonlinear Pharmacokinetics: Causes of Nonlinearity01:22

Nonlinear Pharmacokinetics: Causes of Nonlinearity

714
Nonlinearity in drug pharmacokinetics is caused by various factors influencing how a drug is absorbed, distributed, metabolized, and excreted. Understanding these nonlinear processes is crucial for predicting drug behavior in the body and optimizing drug dosing regimens.
Nonlinear drug absorption can occur when the process is rate-limited by solubility, carrier-mediated transport systems, or saturation of the presystemic gut wall or hepatic metabolism. For instance, high doses of riboflavin...
714

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Stochastic fractional-order memristive fuzzy bam neural networks with time delays and leakage term for finite-time stability analysis.

Scientific reports·2026
Same author

Cuckoo optimization algorithm via Grey Wolf Optimizer for usage in engineering optimization and optimal power flow with renewable energy sources.

Scientific reports·2025
Same author

Improved fault-clearing strategy for large renewable energy systems using advanced optimization and FLC.

Scientific reports·2025
Same author

Finite-time event-triggered sliding mode control for fuzzy singular systems under cyber-attacks.

ISA transactions·2025
Same author

Integrated transmission expansion planning incorporating fault current limiting devices and thyristor-controlled series compensation using meta-heuristic optimization techniques.

Scientific reports·2024
Same author

Security-guaranteed filter design for discrete-time Markovian jump delayed systems subject to deception attacks and sensor saturation.

ISA transactions·2023

相关实验视频

Updated: Jan 23, 2026

Microwave Photonics Systems Based on Whispering-gallery-mode Resonators
12:18

Microwave Photonics Systems Based on Whispering-gallery-mode Resonators

Published on: August 5, 2013

17.5K

在受到攻击的情况下,分析和优化非线性描述器系统中基于观察者的安全滑动模式控制.

Mourad Kchaou, M Syed Ali, Rabeh Abbassi

    IEEE transactions on cybernetics
    |January 21, 2026
    PubMed
    概括

    本研究引入了使用模糊模型和Q学习的弹性控制框架,用于面临攻击的网络物理系统 (CPS). 该方法通过适应性优化对网络物理威胁的控制策略来提高安全性和性能.

    科学领域:

    • 控制系统工程 控制系统工程
    • 网络安全 网络安全
    • 人工智能的人工智能

    背景情况:

    • 网络物理系统 (CPS) 容易受到传感器和执行器攻击,特别是在通信限制下.
    • 非线性描述器系统需要强大的控制策略,以在网络物理威胁期间保持稳定性和性能.
    • 现有的安全框架通常在复杂的攻击场景下与自适应控制和优化作斗争.

    研究的目的:

    • 为非线性描述符网络物理系统在通信限制和网络物理攻击下提出一个弹性控制框架.
    • 开发一种自适应的模糊滑动模式观察器 (SMO) 用于估计具有不匹配前提变量的受损系统状态.
    • 设计一个滑动模式控制器 (SMC),确保闭环可接受性和滑动表面可达性,使用秘书鸟优化算法 (SBOA) 进行优化.

    主要方法:

    • 将Takagi-Sugeno (T-S) 模糊模型与基于Q学习的事件触发机制 (ETM) 集成.
    • 适应性模糊滑动模式观察器 (SMO) 和滑动模式控制器 (SMC) 的开发.
    • 应用秘书鸟优化算法 (SBOA) 来优化控制器和观察者收益以解决非凸的优化问题.

    主要成果:

    • 拟议的框架有效地平衡了运营效率与对网络物理威胁的强有力的保护.
    • 适应性模糊SMO准确地估计了受损的系统状态,即使有不匹配的前提变量.

    更多相关视频

    Contact Mode Atomic Force Microscopy as a Rapid Technique for Morphological Observation and Bacterial Cell Damage Analysis
    05:34

    Contact Mode Atomic Force Microscopy as a Rapid Technique for Morphological Observation and Bacterial Cell Damage Analysis

    Published on: June 30, 2023

    2.3K
    Automation of Mode Locking in a Nonlinear Polarization Rotation Fiber Laser through Output Polarization Measurements
    14:18

    Automation of Mode Locking in a Nonlinear Polarization Rotation Fiber Laser through Output Polarization Measurements

    Published on: February 28, 2016

    11.9K

    相关实验视频

    Last Updated: Jan 23, 2026

    Microwave Photonics Systems Based on Whispering-gallery-mode Resonators
    12:18

    Microwave Photonics Systems Based on Whispering-gallery-mode Resonators

    Published on: August 5, 2013

    17.5K
    Contact Mode Atomic Force Microscopy as a Rapid Technique for Morphological Observation and Bacterial Cell Damage Analysis
    05:34

    Contact Mode Atomic Force Microscopy as a Rapid Technique for Morphological Observation and Bacterial Cell Damage Analysis

    Published on: June 30, 2023

    2.3K
    Automation of Mode Locking in a Nonlinear Polarization Rotation Fiber Laser through Output Polarization Measurements
    14:18

    Automation of Mode Locking in a Nonlinear Polarization Rotation Fiber Laser through Output Polarization Measurements

    Published on: February 28, 2016

    11.9K
  • 在卡车拖车系统上的模拟验证了这种方法在各种攻击场景下保持系统稳定性和性能方面的有效性.
  • 结论:

    • 开发的弹性控制框架显著提高了网络环境中的非线性网络物理系统的安全性.
    • 模糊逻辑,Q学习和滑动模式控制的集成,通过SBOA进行优化,为自适应性安全提供了新的解决方案.
    • 这项工作有助于保护CPS免受复杂的网络物理攻击,确保可靠的系统运行.