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相关概念视频

Control Systems01:10

Control Systems

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...
Feedback control systems01:26

Feedback control systems

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...
Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear.
Controller Configurations01:22

Controller Configurations

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

Time-Domain Interpretation of PD Control

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...
Load-frequency control01:28

Load-frequency control

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...

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相关实验视频

Updated: Jul 7, 2026

Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques
09:01

Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques

Published on: April 4, 2017

固定时间自适应神经网络对不确定的非线性系统进行补偿控制.

Jiahua Ma1, Zhikai Yao2, Wenxiang Deng1

  • 1School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing, 210094, Jiangsu, China.

Neural networks : the official journal of the International Neural Network Society
|May 16, 2025
PubMed
概括

本研究引入了一种新的固定时间自适应神经网络控制方法,以提高具有不确定性的非线性系统的性能. 该方法确保了固定的时间稳定性,克服了复杂系统中的控制限制.

关键词:
适应 适应 适应固定时间控制控制.神经网络的神经网络的神经网络不确定的非线性系统

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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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Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

Published on: October 28, 2022

相关实验视频

Last Updated: Jul 7, 2026

Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques
09:01

Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques

Published on: April 4, 2017

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
06:45

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

Published on: October 28, 2022

科学领域:

  • 控制系统工程 控制系统工程
  • 非线性动力学是一种非线性动力学.
  • 人工智能在控制中

背景情况:

  • 非线性系统中的不确定性阻碍了控制性能.
  • 高级非线性系统带来了重要的控制挑战.
  • 现有的方法可能会受到保守主义或差异性爆炸的影响.

研究的目的:

  • 开发一个固定时间的自适应神经网络补偿控制方法.
  • 为了解决不确定的非线性和参数不确定性.
  • 提高控制性能,确保固定时间稳定性.

主要方法:

  • 为不确定的非线性设计了一个固定时间自适应神经网络 (FTANN).
  • 为参数不确定性开发了一个新的固定时间自适应定律.
  • 在动态表面控制 (DSC) 框架内,集成FTANN和自适应法与增强自适应的固定时间波器.

主要成果:

  • 拟议的控制器保证了所有系统状态的固定时间稳定性,这是由Lyapunov分析证明的.
  • 该方法解决了一些控制设计中固有的"微分爆炸"问题.
  • 通过降低强大的反收益,减少了控制器保守主义.

结论:

  • 新的固定时间自适应神经网络控制方法有效地管理高阶非线性系统中的不确定性.
  • 综合方法确保在固定的时间内确保系统稳定性.
  • 模拟和实验结果验证了控制器的卓越性能.