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相关概念视频

Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

88
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....
88
Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

75
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,...
75
Time-Domain Interpretation of PD Control01:07

Time-Domain Interpretation of PD Control

86
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...
86
Second Order systems II01:18

Second Order systems II

96
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.
96
Multimachine Stability01:25

Multimachine Stability

150
Multimachine stability analysis is crucial for understanding the dynamics and stability of power systems with multiple synchronous machines. The objective is to solve the swing equations for a network of M machines connected to an N-bus power system.
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:
150
Distribution Reliability and Automation01:25

Distribution Reliability and Automation

107
Distribution reliability in electrical power systems is critical for ensuring an uninterrupted power supply to consumers at minimal cost. According to IEEE Standard Terms, reliability is the probability that a device will function without failure over a specified time period or amount of usage. For electric power distribution, this translates to maintaining continuous power supply and addressing customer concerns over power outages. Several indices, as defined by IEEE Standard 1366-2012, are...
107

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相关实验视频

Updated: Jun 18, 2025

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

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Published on: October 28, 2022

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基于中间参数的分布式传感器对一类非线性系统的容错估计.

Chuan Yu1, Qingyu Su1, Jing Sun1

  • 1School of Automation Engineering, Northeast Electric Power University, Jilin, 132012, China.

ISA transactions
|August 2, 2024
PubMed
概括

本研究介绍了一种用于非线性系统的新型分布式容错观察器,有效地估计系统状态和执行器故障,即使有传感器故障. 该方法通过使用健康水平指数过不健康的传感器信号来确保可靠的状态估计.

关键词:
分布式故障估计分布式故障估计宽容错误的观察者是一个宽容错误的观察者.中间变量是一个中间变量.冗余的传感器是多余的

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相关实验视频

Last Updated: Jun 18, 2025

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科学领域:

  • 控制系统工程 控制系统工程
  • 故障诊断和故障容忍能力
  • 非线性系统分析 非线性系统分析

背景情况:

  • 非线性系统容易发生执行器和传感器故障,从而损害其操作完整性.
  • 现有的容错的观察器设计经常与分布式系统和复杂的故障场景作斗争.

研究的目的:

  • 为非线性系统开发一个分布式容错的观测器.
  • 在传感器和执行器故障的情况下,准确估计系统状态和执行器故障.
  • 通过强大的故障检测和补偿来提高系统可靠性.

主要方法:

  • 构建一个分布式观察网络,使用中间参数来处理无法观察的节点.
  • 为每个观察节点实施冗余传感器,以增加测量样本.
  • 开发一种基于传感器健康水平指数的传感器信号处理和分类的新算法.
  • 过不健康的传感器信号并保留健康的信号以进行估计.

主要成果:

  • 拟议的算法有效地过了有缺陷的传感器信号,只保留了健康的信号.
  • 通过使用过的传感器数据来准确估计系统状态和执行器故障.
  • 一个案例研究验证了开发的分布式容错观察者的有效性.

结论:

  • 设计的分布式容错观察器为非线性系统中的状态和执行器故障估计提供了强大的解决方案.
  • 传感器健康水平指数和过算法提高了对传感器故障的故障容忍度.
  • 该方法为关键的非线性系统提供了更好的可靠性和性能.