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相关概念视频

State Space Representation01:27

State Space Representation

203
The frequency-domain technique, commonly used in analyzing and designing feedback control systems, is effective for linear, time-invariant systems. However, it falls short when dealing with nonlinear, time-varying, and multiple-input multiple-output systems. The time-domain or state-space approach addresses these limitations by utilizing state variables to construct simultaneous, first-order differential equations, known as state equations, for an nth-order system.
Consider an RLC circuit, a...
203
Classification of Systems-II01:31

Classification of Systems-II

139
Continuous-time systems have continuous input and output signals, with time measured continuously. These systems are generally defined by differential or algebraic equations. For instance, in an RC circuit, the relationship between input and output voltage is expressed through a differential equation derived from Ohm's law and the capacitor relation,
139
Linear time-invariant Systems01:23

Linear time-invariant Systems

245
A system is linear if it displays the characteristics of homogeneity and additivity, together termed the superposition property. This principle is fundamental in all linear systems. Linear time-invariant (LTI) systems include systems with linear elements and constant parameters.
The input-output behavior of an LTI system can be fully defined by its response to an impulsive excitation at its input. Once this impulse response is known, the system's reaction to any other input can be...
245
BIBO stability of continuous and discrete -time systems01:24

BIBO stability of continuous and discrete -time systems

382
System stability is a fundamental concept in signal processing, often assessed using convolution. For a system to be considered bounded-input bounded-output (BIBO) stable, any bounded input signal must produce a bounded output signal. A bounded input signal is one where the modulus does not exceed a certain constant at any point in time.
To determine the BIBO stability, the convolution integral is utilized when a bounded continuous-time input is applied to a Linear Time-Invariant (LTI) system....
382
State Space to Transfer Function01:21

State Space to Transfer Function

197
The conversion of state-space representation to a transfer function is a fundamental process in system analysis. It provides a method for transitioning from a time-domain description to a frequency-domain representation, which is crucial for simplifying the analysis and design of control systems.
The transformation process begins with the state-space representation, characterized by the state equation and the output equation. These equations are typically represented as:
197
Signal and System01:26

Signal and System

643
A signal x(t) is a set of data or a time function representing a variable of interest. Signals typically convey information about a phenomenon, such as atmospheric temperature, humidity, human voice, television images, a dog's bark, or birdsongs. More generally, a signal can be a function of more than one independent variable. For instance, images depend on horizontal and vertical positions and can be regarded as two-dimensional signals. However, this text will focus on one-dimensional...
643

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相关实验视频

Updated: Jun 21, 2025

Design and Analysis for Fall Detection System Simplification
08:05

Design and Analysis for Fall Detection System Simplification

Published on: April 6, 2020

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在时间延迟信息交换下的多个传感器系统的分布式状态观察器.

Wen Fang1, Fanglai Zhu1

  • 1College of Electronics and Information Engineering, Tongji University, Shanghai 201804, China.

Sensors (Basel, Switzerland)
|July 13, 2024
PubMed
概括
此摘要是机器生成的。

这项研究为具有时间延迟的线性时间不变系统设计了分布式观测器. 该方法通过在观察者错误动态中实现非对称稳定性来确保准确的状态估计,即使有通信延迟.

关键词:
利亚普诺夫的稳定理论.分布式观察者分布式观察者一个线性矩阵不等式.多个传感器多个传感器.时间延迟时间延迟

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科学领域:

  • 控制系统工程 控制系统工程
  • 网络系统理论 网络系统理论
  • 应用数学 应用数学 应用数学

背景情况:

  • 分布式观察者对于复杂系统中的状态估计至关重要.
  • 信息交换的时间延迟对观察员的表现构成重大挑战.
  • 具有多个传感器的线性时间不变 (LTI) 系统需要强大的估计技术.

研究的目的:

  • 为已知时间延迟的LTI系统设计分布式观察器.
  • 通过有效地拒绝时间延迟来确保非对称状态估计.
  • 开发一种方法来保证观察者错误动态的稳定性.

主要方法:

  • 将目标系统重写为连接形式,以建立受延迟状态影响的子系统.
  • 构建一个分布式的观察器,将每个子系统的时间延迟纳入其中.
  • 根据可观测的正规分解定理,应用一个等效状态转换.
  • 使用线性矩阵不等式 (LMI) 和一个莱普诺夫函数候选项进行稳定性分析.

主要成果:

  • 一个分布式观测器设计,在存在时间延迟的情况下实现非对称状态估计.
  • 用利亚普诺夫稳定理论证明观察者误差动态系统的非对称稳定性.
  • 通过建立LMI的可行解决方案来确定观察者收益.
  • 通过模拟示例验证拟议方法的有效性.

结论:

  • 拟议的分布式观察员设计有效地处理LTI系统中的时间延迟.
  • 基于LMI的方法保证了观察者错误动态的非对称稳定性.
  • 该方法提供了一个可靠的框架,用于在有通信延迟的网络系统中估计状态.