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相关概念视频

Feedback control systems01:26

Feedback control systems

281
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...
281
Time-Domain Interpretation of PD Control01:07

Time-Domain Interpretation of PD Control

83
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...
83
Control Systems01:10

Control Systems

1.0K
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...
1.0K
PI Controller: Design01:24

PI Controller: Design

199
Proportional Integral (PI) controllers are a fundamental component in modern control systems, widely used to enhance performance and mitigate steady-state errors. They are particularly effective in applications such as automatic brightness adjustment on smartphones, where they excel at mitigating steady-state errors for step-function inputs. Unlike PD controllers, which require time-varying errors to function optimally, PI controllers leverage their integral component to address residual...
199
Controller Configurations01:22

Controller Configurations

85
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...
85
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

96
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
96

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相关实验视频

Updated: Jun 3, 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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控制输入约束和故障下的非线性系统的增强控制:基于神经网络的综合模糊滑动模式方法.

Guangyi Yang1, Stelios Bekiros2, Qijia Yao3

  • 1Information Center, Hunan Institute of Metrology and Test, Changsha 410014, China.

Entropy (Basel, Switzerland)
|January 8, 2025
PubMed
概括
此摘要是机器生成的。

本研究介绍了非线性系统的新型控制方法,结合神经网络和模糊逻辑来解决执行器故障和局限性. 这种方法确保了有限时间稳定性和在现实应用中强大的性能.

关键词:
控制输入约束控制输入约束控制故障,控制故障.有限时间稳定性.模糊的逻辑模糊的逻辑整体滑动表面的整体滑动表面神经网络估计器的神经网络估计器

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相关实验视频

Last Updated: Jun 3, 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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科学领域:

  • 控制系统工程 控制系统工程
  • 在工程领域的人工智能.
  • 非线性系统动态 非线性系统动态

背景情况:

  • 现有的控制技术往往忽视了系统故障和物理限制,阻碍了现实世界的应用.
  • 需要先进的控制策略,以适应实际系统中的执行器故障和约束.

研究的目的:

  • 为非线性系统开发一种创新的控制方法,以稳定处理控制执行器故障和物理限制.
  • 为了提高系统的适应性和减少聊天,使用具有模糊逻辑调节的智能观察员来提高系统的适应性.

主要方法:

  • 一个基于神经网络的滑动模式控制算法,与模糊逻辑系统集成.
  • 一个智能观察者结合了一个模糊逻辑引擎来管理执行器故障和限制.
  • 有限时间稳定性分析以验证控制设计.

主要成果:

  • 拟议的控制器有效地保持系统调节,尽管控制输入的限制和故障.
  • 具有模糊逻辑的智能观察者减少了系统的喋喋不休,提高了适应性.
  • 证明了闭环系统的有限时间收和稳定性.

结论:

  • 开发的控制策略为面临执行器故障和局限性的非线性系统提供了强大的解决方案.
  • 该方法确保了有限时间稳定性和自主和非自主系统的有效性能.
  • 这项研究促进了控制系统在具有挑战性的现实场景中的实际实施.