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相关概念视频

Feedback control systems01:26

Feedback control systems

319
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...
319
Open and closed-loop control systems01:17

Open and closed-loop control systems

767
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...
767
Linear time-invariant Systems01:23

Linear time-invariant Systems

263
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...
263
Transfer Function in Control Systems01:21

Transfer Function in Control Systems

517
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...
517
Time-Domain Interpretation of PD Control01:07

Time-Domain Interpretation of PD Control

120
Proportional-Derivative (PD) control is a widely used control method in various engineering systems to enhance stability and performance. In a system with only proportional control, common issues include high maximum overshoot and oscillation, observed in both the error signal and its rate of change. This behavior can be divided into three distinct phases: initial overshoot, subsequent undershoot, and gradual stabilization.
Consider the example of control of motor torque. Initially, a positive...
120
Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

84
Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
84

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相关实验视频

Updated: Jul 11, 2025

WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control
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事件触发的集成滑动模式控制不确定的网络线性控制系统与量子化.

Xinggui Zhao1, Bo Meng1, Zhen Wang1

  • 1College of Mathematics and Systems Science, Shandong University of Science and Technology, Qingdao 266590, China.

Mathematical biosciences and engineering : MBE
|November 3, 2023
PubMed
概括
此摘要是机器生成的。

本研究介绍了一种集成滑动模式 (ISM) 控制器,用于具有不确定性的联网线性系统. 新型事件触发控制减少了网络负担和能源损失,同时确保了系统稳定性.

关键词:
事件触发的控制是事件触发的.整体滑动模式控制器 滑动模式控制器网络化系统 网络化系统量子化反控制控制 量子化反控制

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相关实验视频

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科学领域:

  • 控制系统工程 控制系统工程
  • 网络化系统 网络化系统
  • 不确定系统 不确定系统

背景情况:

  • 网络系统面临的挑战是非周期性采样数据和不确定性.
  • 集成滑动模式 (ISM) 控制为强大的系统稳定提供了潜力.
  • 现有的方法可能无法充分解决网络负担和能源效率问题.

研究的目的:

  • 为具有匹配和不匹配不确定性的联网线性系统设计ISM控制器.
  • 开发一个事件触发 (ET) 机制来减少数据传输.
  • 为了进一步降低网络负载和节省能源,将量子化纳入.

主要方法:

  • 重新设计了名义控制器增益,以实现非对称稳定性.
  • 间歇性控制使用达到法为有限时间可达性.
  • 事件触发的条件来自实际的SM存在的测量误差.
  • 量化方案以减少网络传输负担.
  • 通过事件间时间的正下限来确保没有Zeno行为.

主要成果:

  • 拟议的ISM控制器保证了不确定的网络线性系统的非对称稳定性.
  • 事件触发条件确保了实际滑动模式的存在.
  • 综合量子化方案有效降低了网络传输负担.
  • 没有观察到Zeno行为,证实了系统的可行性.
  • 与传统的ISMC相比,控制法减轻了网络负担,减少了输电能耗.

结论:

  • 开发的ISM控制器具有事件触发和量子化控制,对于不确定的网络线性系统是有效的.
  • 该方法显著降低了网络负载和能源消耗.
  • 模拟结果验证了拟议的方法的实际应用.