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相关概念视频

Feedback control systems01:26

Feedback control systems

303
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...
303
One-Degree-of-Freedom System01:24

One-Degree-of-Freedom System

479
In mechanical engineering, one-degree-of-freedom systems form the basis of a wide range of electrical and mechanical components. Using these models, engineers can predict the behavior of various parts in a larger system, which gives them insight into how different forces interact with each other.
A one-degree-of-freedom system is defined by an independent variable that determines its state and behavior. One example of a one-degree-of-freedom system is a simple harmonic oscillator, such as a...
479
Time-Domain Interpretation of PD Control01:07

Time-Domain Interpretation of PD Control

87
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...
87
Control Systems01:10

Control Systems

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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...
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Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

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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,...
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Second Order systems II01:18

Second Order systems II

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In an underdamped second-order system, where the damping ratio ζ is between 0 and 1, a unit-step input results in a transfer function that, when transformed using the inverse Laplace method, reveals the output response. The output exhibits a damped sinusoidal oscillation, and the difference between the input and output is termed the error signal. This error signal also demonstrates damped oscillatory behavior. Eventually, as the system reaches a steady state, the error diminishes to zero.
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相关实验视频

Updated: Jun 20, 2025

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
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对非线性宏微运动系统的扩展性歇斯底里观测基于自适应的稳健控制方法.

Jianfeng Sun1, Xuesong Chen1

  • 1School of Mathematics and Statistics, Guangdong University of Technology, No. 161, Yinglong Road, Tianhe District, Guangzhou, 510520, Guangdong Province, China.

ISA transactions
|July 21, 2024
PubMed
概括
此摘要是机器生成的。

一种新的有限时间自适应性强有力的控制方法增强了对宏微运动平台的压电歇斯底里补偿. 这种先进的控制确保了稳定的跟踪,并最大限度地减少了复杂的运动系统中的错误.

关键词:
扩展状态观察者观察者有限时间的有限时间.歇斯底里斯模型模型宏观微观复合运动系统强大的自适应控制.

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科学领域:

  • 机器人和控制系统 机器人和控制系统
  • 材料科学 (压电材料)
  • 机械工程 机械工程

背景情况:

  • 宏微复合运动平台由于压电歇斯底里表现出复杂的动态.
  • 由于固有的非线性和参数不确定性,对这些系统的准确控制具有挑战性.
  • 现有的控制方法往往在歇斯底里存在时难以准确跟踪和稳定.

研究的目的:

  • 为宏微复合运动平台提出一种新的有限时间自适应强健控制 (TARC) 方法.
  • 为了解决和补偿压电歇斯底里斯非线性.
  • 为了提高追踪精度和系统稳定性.

主要方法:

  • 为宏微复合运动系统构建动态模型.
  • 扩展歇斯底里观察器的设计,以估计系统状态 (位移和速度).
  • 制定适应性强度控制法,以减轻歇斯底里模型参数中的不确定性.

主要成果:

  • 拟议的TARC方法实现了指数趋同,确保了有限时间的稳定性.
  • 控制方法通过设置系统的带宽来证明减少增益调整的计算负载.
  • 与其他方法相比,模拟显示出更高的性能,跟踪更稳定,错误减少.

结论:

  • 有限时间的自适应性强大的控制方法有效地弥补了宏微运动平台中的压电歇斯底里.
  • 拟议的基于观察者的控制策略提高了系统的稳定性和跟踪精度.
  • 这种方法为先进的运动控制应用提供了计算效率高和稳定的解决方案.