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相关概念视频

Time-Domain Interpretation of PD Control01:07

Time-Domain Interpretation of PD Control

186
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...
186
Feedback control systems01:26

Feedback control systems

442
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...
442
Control Systems01:10

Control Systems

1.4K
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...
1.4K
Time and frequency -Domain Interpretation of PI Control01:27

Time and frequency -Domain Interpretation of PI Control

208
Proportional-Integral (PI) controllers are essential in many control systems to improve stability and performance. They are commonly used in everyday devices like thermostats to enhance system damping and reduce steady-state error. When the zero in the controller's transfer function is optimally placed, the system benefits significantly in terms of stability and accuracy.
Acting as a low-pass filter, the PI controller slows the system's response and extends settling times. This requires...
208
PD Controller: Design01:26

PD Controller: Design

360
In automotive engineering, car suspension systems often employ Proportional Derivative (PD) controllers to enhance performance. PD controllers are utilized to adjust the damping force in response to road conditions. A controller, acting as an amplifier with a constant gain, demonstrates proportional control, with output directly mirroring input.
Designing a continuous-data controller requires selecting and linking components like adders and integrators, which are fundamental in Proportional,...
360
Time and frequency -Domain Interpretation of Phase-lag Control01:21

Time and frequency -Domain Interpretation of Phase-lag Control

154
Phase-lag controllers are widely used in control systems to improve stability and reduce steady-state errors. A dimmer switch controlling the brightness of a light bulb serves as a practical example of phase-lag control, gradually adjusting the bulb's brightness. Mathematically, phase-lag control or low-pass filtering is represented when the factor 'a' is less than 1.
Phase-lag controllers do not place a pole at zero, but instead influence the steady-state error by amplifying any...
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相关实验视频

Updated: Sep 20, 2025

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
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基于命令过的机器人操纵器的规定的时间自适应事件触发控制.

Yongling Xia1, Yanbin Liu1, Weichao Sun2

  • 1School of Harbin Institute of Technology, Harbin 150000, China.

ISA transactions
|May 23, 2025
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种新的控制方法,用于不确定的机器人操纵器,确保在设定的时间内稳定. 该方法使用神经网络和事件触发器来管理不确定性并节省资源.

关键词:
命令过器是一个命令过器.事件触发的事件触发.神经网络的神经网络的神经网络规定时间的规定时间.

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科学领域:

  • 机器人技术 机器人技术 机器人技术
  • 控制系统工程 控制系统工程
  • 人工智能的人工智能

背景情况:

  • 机器人操纵器控制受到模型不确定性和外部干扰的挑战.
  • 在预定义的时间框架内实现精确的控制对于许多应用程序至关重要.
  • 现有的方法经常遭受复杂性爆炸和过错误.

研究的目的:

  • 为不确定的操纵系统开发一种新的规定的时间适应性事件触发控制方案.
  • 为了有效地解决模型不确定性和外部干扰.
  • 为了在用户定义的沉降时间内确保稳定性,而没有复杂性爆炸问题.

主要方法:

  • 利用神经网络来处理操纵模型的不确定性.
  • 开发了一种零碎的功能,以达到足够的规定的时间稳定性条件.
  • 实施了一个错误补偿策略来管理过器错误.
  • 引入了对外部干扰的适应性估计策略.
  • 整合了一个事件触发机制,以优化通信资源.

主要成果:

  • 成功提出了一种新的规定的时间适应事件触发控制方案.
  • 该方法将收域和结算时间解为预设参数.
  • 这种方法避免了"复杂性爆炸",并弥补了过器错误.
  • 外部干扰被适应性补偿,并节省通信资源.
  • 模拟结果证明了拟议的控制方法的优越性.

结论:

  • 拟议的控制方案为不确定的操纵系统实现了规定的时间稳定性.
  • 该方法有效地处理模型不确定性,外部干扰和过错误.
  • 事件触发机制提高了通信效率,使其适合于现实世界的应用.