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相关概念视频

State Space to Transfer Function01:21

State Space to Transfer Function

552
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:
552
Transfer Function to State Space01:23

Transfer Function to State Space

748
State-space representation is a powerful tool for simulating physical systems on digital computers, necessitating the conversion of the transfer function into state-space form. Consider an nth-order linear differential equation with constant coefficients, like those encountered in an RLC circuit. The state variables are selected as the output and its n−1 derivatives. Differentiating these variables and substituting them back into the original equation produces the state equations.
In an RLC...
748
Transient and Steady-state Response01:24

Transient and Steady-state Response

507
In control systems, test signals are essential for evaluating performance under various conditions. The ramp function is effective for systems undergoing gradual changes, while the step function is suitable for assessing systems facing sudden disturbances. For systems subjected to shock inputs, the impulse function is the most appropriate test signal.
These test signals are integral in designing control systems to exhibit two key performance aspects: transient response and steady-state...
507
State Space Representation01:27

State Space Representation

519
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...
519
BIBO stability of continuous and discrete -time systems01:24

BIBO stability of continuous and discrete -time systems

880
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....
880
Linear time-invariant Systems01:23

Linear time-invariant Systems

863
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...
863

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相关实验视频

Updated: Jan 13, 2026

Quantum State Engineering of Light with Continuous-wave Optical Parametric Oscillators
09:23

Quantum State Engineering of Light with Continuous-wave Optical Parametric Oscillators

Published on: May 30, 2014

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基于Zonotope的状态估计,用于带有马尔科夫跳跃过程的提升转换器系统.

Chaoxu Guan1, You Li1, Zhenyu Wang2

  • 1College of Mechanical Engineering, Jiaxing University, Jiaxing 314001, China.

Micromachines
|October 29, 2025
PubMed
概括

这项研究介绍了马尔科夫跳跃推进转换器的基于zonotope的状态估计. 适应性事件触发方法提高了稳定性,并节省了功率电子系统的通信资源.

关键词:
马尔科夫跳跃过程的过程适应性的事件触发机制.增强转换器的转换器.国家估计估计.区域位素的区域位素.

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Dynamic Clamp Methods to Investigate Impaired Neuronal Excitability Associated with Autism

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相关实验视频

Last Updated: Jan 13, 2026

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科学领域:

  • 动力电子和控制系统
  • 非线性系统分析 非线性系统分析
  • 随机系统 随机系统 随机系统

背景情况:

  • 直流-直流增压转换器对于功率电子应用,如可再生能源和电动汽车至关重要.
  • 不线性动态和提升转换器中的不确定性需要强大的状态估计技术.
  • 马尔科夫跳跃系统模型随机行为和切换在动态系统.

研究的目的:

  • 开发一种基于zonotope的状态估计方法,用于带有马尔科夫跳跃过程的提升转换器系统.
  • 将时间延迟,干扰和噪音整合到一个通用的离散时间模型中.
  • 实施适应性事件触发机制,以实现高效的数据传输.

主要方法:

  • 模拟提升转换器作为马尔科夫跳跃系统,具有不确定性和延迟.
  • 为增强系统设计一个H∞性能观察器.
  • 开发一个 zonotopic 集合成员估计算法,以限制系统状态.
  • 使用适应性事件触发机制来优化数据传输.

主要成果:

  • 拟议的区域位估计实际上包含了马尔科夫跳动力学下的所有系统状态.
  • 适应性事件触发机制显著降低了通信负载,同时保持了估计准确性.
  • H∞性能标准确保了对干扰和噪音的稳定性.
  • 数字模拟验证了开发的状态估计方法的有效性.

结论:

  • 基于zonotope的状态估计为在随机条件下运行的提升转换器提供了强大的解决方案.
  • 适应性事件触发策略提高了网络控制系统的通信效率.
  • 这种方法有助于现代电力电子系统的可靠操作和控制.