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相关概念视频

Linear time-invariant Systems01:23

Linear time-invariant Systems

412
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...
412
Sampling Continuous Time Signal01:11

Sampling Continuous Time Signal

348
In signal processing, a continuous-time signal can be sampled using an impulse-train sampling technique, followed by the zero-order hold method. Impulse-train sampling involves the use of a periodic impulse train, which consists of a series of delta functions spaced at regular intervals determined by the sampling period. When a continuous-time signal is multiplied by this impulse train, it generates impulses with amplitudes corresponding to the signal's values at the sampling points.
In the...
348
Basic Discrete Time Signals01:16

Basic Discrete Time Signals

304
The unit step sequence is defined as 1 for zero and positive values of the integer n. This sequence can be graphically displayed using a set of eight sample points, showing a step function starting from n=0 and remaining constant thereafter.
The unit impulse or sample sequence is mathematically expressed as zero for all n values except at n=0, where it is one. The unit impulse sequence, denoted by δ(n), is the first difference of the unit step sequence, while the unit step sequence u(n) is...
304
Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

131
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....
131
BIBO stability of continuous and discrete -time systems01:24

BIBO stability of continuous and discrete -time systems

514
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....
514
Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

125
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,...
125

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在嵌入式系统中的离散单边受约束扩展卡尔曼波器.

Leonardo Herrera1, Rodrigo Méndez-Ramírez2

  • 1Independent Researcher, Monterey, CA 93943, USA.

Sensors (Basel, Switzerland)
|August 14, 2025
PubMed
概括
此摘要是机器生成的。

一个新的离散单边约束扩展卡尔曼波器 (DUCEKF) 算法增强了对具有单边约束的混合机械系统的状态估计. 这种方法在模拟和实验中优于标准的扩展卡尔曼波器 (EKF).

关键词:
扩展卡尔曼波器 扩展卡尔曼波器数字到模拟转换器转换器dsPICIC 是一个特殊的产品.嵌入式系统嵌入式系统微控制器上的微控制器单方面制约的限制.

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科学领域:

  • 控制系统工程 控制系统工程
  • 机器人技术 机器人技术 机器人技术
  • 机械工程 机械工程

背景情况:

  • 卡尔曼波器 (KF) 是平滑系统最佳状态估计的基石.
  • 现有的KF变体经常与非光滑系统扎,特别是那些具有单边约束的系统.

研究的目的:

  • 引入离散单边约束扩展卡尔曼波器 (DUCEKF) 算法.
  • 将扩展卡尔曼波器 (EKF) 的功能扩展到具有单边约束的混合机械系统,其特点是不平滑的位置和不连续的速度.

主要方法:

  • 开发离散单边约束扩展卡尔曼波器 (DUCEKF) 算法.
  • 应用利亚普诺夫稳定理论来证明估计误差稳定性.
  • 使用模拟和实验验证对扩展卡尔曼波器 (EKF) 的比较分析.

主要成果:

  • 与EKF相比,DUCEKF算法在对具有单边约束的系统进行状态估计方面表现优越.
  • 模拟证实了DUCEKF在处理非平滑和不连续的系统动态方面的有效性.
  • 使用嵌入式系统和DAC硬件进行的实验验证证证了模拟结果.

结论:

  • DUCEKF算法成功地将最佳状态估计扩展到具有单边约束的混合机械系统.
  • 拟议的方法为非平滑动态系统中的状态估计挑战提供了强大的解决方案.
  • 该研究通过模拟和现实世界实验验证实了DUCEKF的实用性.