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

Multimachine Stability01:25

Multimachine Stability

188
Multimachine stability analysis is crucial for understanding the dynamics and stability of power systems with multiple synchronous machines. The objective is to solve the swing equations for a network of M machines connected to an N-bus power system.
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:
188
Cluster Sampling Method01:20

Cluster Sampling Method

12.0K
Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
12.0K
Sequence Networks of Rotating Machines01:24

Sequence Networks of Rotating Machines

123
A Y-connected synchronous generator, grounded through a neutral impedance, is designed to produce balanced internal phase voltages with only positive-sequence components. The generator's sequence networks include a source voltage that is exclusively in the positive-sequence network. The sequence components of line-to-ground voltages at the generator terminals illustrate this configuration.
Zero-sequence current induces a voltage drop across the generator's neutral impedance and other...
123
Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

668
Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...
668
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

127
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
127
Load-frequency control01:28

Load-frequency control

187
Load-frequency control (LFC) is vital for maintaining power system stability, ensuring that frequency and power flows remain within acceptable limits during load changes. Turbine-governor control eliminates rotor accelerations and decelerations following load changes. However, a steady-state frequency error persists when the change in the turbine-governor reference setting is zero. In an interconnected power system, each area agrees to export or import a scheduled amount of power through...
187

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

Integrative cross-sample alignment and spatially differential gene analysis for spatial transcriptomics.

Nature communications·2026
Same author

A general framework for neural delay differential equations with various delay types.

Chaos (Woodbury, N.Y.)·2026
Same author

Utilizing Causal Network Markers to Identify Tipping Points ahead of Critical Transition.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2025
Same author

Reordered hierarchical complexity in ecosystems with delayed interactions.

PNAS nexus·2025
Same author

Transfer learning of multicellular organization via single-cell and spatial transcriptomics.

PLoS computational biology·2025
Same author

Author Correction: Emerging opportunities and challenges for the future of reservoir computing.

Nature communications·2024

相关实验视频

Updated: Jul 17, 2025

Disruption of Frontal Lobe Neural Synchrony During Cognitive Control by Alcohol Intoxication
09:26

Disruption of Frontal Lobe Neural Synchrony During Cognitive Control by Alcohol Intoxication

Published on: February 6, 2019

18.8K

通过适应性控制部分网络,在多集群网络中合的脱同步振荡器.

Kaidian Wang1,2, Luan Yang2, Shijie Zhou2,3

  • 1School of Mathematical Sciences, Shandong University, Jinan, Shandong 250100, China.

Chaos (Woodbury, N.Y.)
|September 7, 2023
PubMed
概括

本研究提出了一个适应性控制方案,以实现连接网络中的脱同步,即使有反延迟. 对于拥有三个或更多集群的网络来说,控制单个集群是不够的.

更多相关视频

Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons
07:59

Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons

Published on: June 9, 2023

1.4K
Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator
06:04

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator

Published on: February 14, 2025

494

相关实验视频

Last Updated: Jul 17, 2025

Disruption of Frontal Lobe Neural Synchrony During Cognitive Control by Alcohol Intoxication
09:26

Disruption of Frontal Lobe Neural Synchrony During Cognitive Control by Alcohol Intoxication

Published on: February 6, 2019

18.8K
Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons
07:59

Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons

Published on: June 9, 2023

1.4K
Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator
06:04

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator

Published on: February 14, 2025

494

科学领域:

  • 神经科学是一个神经科学.
  • 控制理论 控制理论
  • 网络科学 网络科学

背景情况:

  • 结合网络同步在各种生物和人工系统中起着至关重要的作用.
  • 实现受控脱同步对于理解和治疗神经系统疾病至关重要.
  • 现有的控制方案经常因反延迟和部分网络控制而扎.

研究的目的:

  • 引入一种新的自适应控制方案,以实现在有反延迟的联网网络中的脱同步.
  • 调查该方案在部分控制网络中的有效性,包括多个集群的网络.
  • 分析时间延迟和相互连接对网络稳定性的影响.

主要方法:

  • 开发一个适应性控制方案,包括反延迟.
  • 使用数字和严格分析验证超越特征方程的验证.
  • 适用于两个和多个集群的合神经网络.
  • 对不同延迟和连接参数下的不连贯状态的稳定性的研究.

主要成果:

  • 拟议的自适应控制方案有效地实现了与反延迟相结合的网络中的脱同步.
  • 仅控制一个集群已被证明在有三个或更多集群的网络中对脱同步无效.
  • 时间延迟和互连性显著影响不连贯状态的稳定性.

结论:

  • 适应性控制方案为诱导复杂网络中的脱同步提供了一种可行的方法.
  • 了解单个集群控制的局限性对于多个集群网络干预至关重要.
  • 研究结果提供了深度大脑刺激的见解,并建议用于神经退行性疾病治疗的适应性反策略.