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相关概念视频

Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

68
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,...
68
State Space Representation01:27

State Space Representation

168
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...
168
Transfer Function to State Space01:23

Transfer Function to State Space

201
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...
201
Linear time-invariant Systems01:23

Linear time-invariant Systems

222
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...
222
Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

87
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....
87
Second Order systems II01:18

Second Order systems II

92
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.
92

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Generation and Coherent Control of Pulsed Quantum Frequency Combs
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对线性动态系统的量化状态估计.

Ramchander Rao Bhaskara1, Manoranjan Majji1, Felipe Guzmán2

  • 1Department of Aerospace Engineering, Texas A&M University, College Station, TX 77843, USA.

Sensors (Basel, Switzerland)
|October 16, 2024
PubMed
概括
此摘要是机器生成的。

这项研究通过计算有限精度错误来增强嵌入式系统的状态估计. 优化的算法提高了资源有限的应用程序的性能和准确性.

关键词:
在FPGA中,FPGA是指FPGA.卡尔曼过器可以过.具有有限精度的精度.有光学传感器.量化过是用量化过的方式进行的.国家估计估计.

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相关实验视频

Last Updated: Jun 10, 2025

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Quantum State Engineering of Light with Continuous-wave Optical Parametric Oscillators
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科学领域:

  • 控制系统工程 控制系统工程
  • 嵌入式系统 嵌入式系统
  • 数字分析 数字分析

背景情况:

  • 状态估计对于动态系统至关重要,但对资源有限的嵌入式系统具有挑战性.
  • 嵌入式系统中的有限精度算法引入了影响估计准确性的数值错误.

研究的目的:

  • 重构最小平均平方估计算法以包括有限精度的数值错误.
  • 开发和评估固定点实现的量化估计算法.
  • 分析数字精度和过器精度之间的性能权衡.

主要方法:

  • 提出了最小平方批量估计,顺序卡尔曼和平方根过算法的量化版本.
  • 进行了数值模拟,以比较性能与标准配方.
  • 使用平稳状态共变性分析,以数字精度评估性能权衡.
  • 在FPGA-SoC硬件上实现了一个固定点加速状态估计架构.

主要成果:

  • 拟议的定量化算法比标准过器表现出性能改进.
  • 稳定状态共差分析提供了基于数值精度的可实现波器精度的见解.
  • 在FPGA-SoC上的硬件实现显示了与双重精度MATLAB实现的性能相似的性能.
  • 实验结果验证了模拟量子化错误的意义.

结论:

  • 建模量子化错误对于固定点嵌入式系统中准确的状态估计至关重要.
  • 开发的固定点加速架构为光机械传感提供了可行的解决方案.
  • 该研究为优化资源有限环境中的状态估计提供了一个框架.