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相关概念视频

Feedback control systems01:26

Feedback control systems

657
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...
657
Linear time-invariant Systems01:23

Linear time-invariant Systems

839
A system is linear if it displays the characteristics of homogeneity and additivity, together termed the superposition property. This principle is fundamental in all linear systems. Linear time-invariant (LTI) systems include systems with linear elements and constant parameters.
The input-output behavior of an LTI system can be fully defined by its response to an impulsive excitation at its input. Once this impulse response is known, the system's reaction to any other input can be...
839
Load-frequency control01:28

Load-frequency control

584
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...
584
Phase-lead and Phase-lag Controllers01:22

Phase-lead and Phase-lag Controllers

503
Understanding the working function of different types of controllers can be illustrated with practical analogies, such as adjusting a stereo's volume equalizer. Cranking up the bass involves a phase-lead controller, which functions as a high-pass filter, while increasing the treble uses a phase-lag controller, which acts as a low-pass filter. PD controllers, similar to high-pass filters, enhance the system's response to high-frequency components. PI controllers, akin to low-pass...
503
Open and closed-loop control systems01:17

Open and closed-loop control systems

1.5K
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...
1.5K
Controller Configurations01:22

Controller Configurations

330
Controller configurations are crucial in a car's cruise control system because they manage speed over time to maintain a consistent pace regardless of road conditions, thereby meeting design goals. In traditional control systems, fixed-configuration design involves predetermined controller placement. System performance modifications are known as compensation.
Control-system compensation involves various configurations, most commonly series or cascade compensation, in which the controller...
330

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相关实验视频

Updated: Jan 7, 2026

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
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Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

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通过模糊的神经自适应滑动控制,高阶非线性多代理系统的规定的时间领袖-追随者同步.

Safeer Ullah1, Muhammad Zeeshan Babar2, Sultan Alghamdi3,4

  • 1Department of Electrical Engineering, Quaid-e-Azam College of Engineering & Technology, Sahiwal 57000, Pakistan.

Sensors (Basel, Switzerland)
|December 31, 2025
PubMed
概括
此摘要是机器生成的。

本研究提出了一个新的控制框架,用于在设定的时间内更快,更稳定的非线性多代理系统 (MAS) 的同步. 它使用模糊的神经网络和自适应控制来有效处理不确定性和干扰.

关键词:
适应性强有力的控制.模糊的神经网络 模糊的神经网络领导者跟随者共识的共识多代理系统是多代理系统.不单一的终端滑动模式控制器规定的时间同步.

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相关实验视频

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科学领域:

  • 控制理论 控制理论
  • 人工智能的人工智能
  • 系统工程 系统工程

背景情况:

  • 多代理系统 (MAS) 的同步对于协调行为至关重要.
  • 现有的方法在不确定性下与规定的时间控制作斗争.

研究的目的:

  • 开发一种新的控制框架,用于非线性MAS的规定的时间同步.
  • 确保领导者和追随者在用户定义的时间内达成共识,无论最初的状态如何.

主要方法:

  • 模糊神经网络 (FNN) 的集成用于在线非线性近似.
  • 使用一个强大的非单元终端滑动模式控制器 (NTSMC).
  • 采用自适应更新定律和利亚普诺夫稳定性分析.

主要成果:

  • 实现了对高阶非线性MAS的规定的时间同步.
  • 证明了对参数不确定性和外部干扰的增强强性.
  • 与传统方法相比,模拟证实了更快的融合和适应性.

结论:

  • 拟议的FNN-NTSMC框架为MAS同步提供了卓越的性能.
  • 对不确定性和干扰的有效处理确保了可靠的共识.
  • 该方法在用户定义的时间框架内提供精确的控制.