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相关概念视频

Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

108
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,...
108
BIBO stability of continuous and discrete -time systems01:24

BIBO stability of continuous and discrete -time systems

448
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....
448
Time-Domain Interpretation of PD Control01:07

Time-Domain Interpretation of PD Control

147
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...
147
Second Order systems II01:18

Second Order systems II

137
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.
137
Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

117
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....
117
Linear time-invariant Systems01:23

Linear time-invariant Systems

298
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...
298

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相关实验视频

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A Human-machine-interface Integrating Low-cost Sensors with a Neuromuscular Electrical Stimulation System for Post-stroke Balance Rehabilitation
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对于延迟分数级复杂值神经网络的固定偏差稳定和同步.

Bingrui Zhang1, Jin-E Zhang1

  • 1School of Mathematics and Statistics, Hubei Normal University, Huangshi 435002, China.

Mathematical biosciences and engineering : MBE
|June 16, 2023
PubMed
概括

本研究探讨了延迟分数顺序复杂值神经网络的固定偏差稳定和同步. 新条件确保使用线性不连续控制器的稳定性和同步性.

科学领域:

  • 具有复杂价值的神经网络.
  • 分数顺序的系统是分数顺序的系统.
  • 控制理论 控制理论 控制理论

背景情况:

  • 分数顺序系统比整数顺序系统提供了增强的建模功能.
  • 复杂值的神经网络对于处理复杂数据至关重要.
  • 同步和稳定是神经网络研究中的关键挑战.

研究的目的:

  • 研究有延迟的分数级复杂值神经网络的固定偏差稳定和同步.
  • 为了实现这些目标,开发一个线性不连续控制器.
  • 通过模拟来验证拟议的理论框架.

主要方法:

  • 分数计算原理的应用.
  • 使用固定偏差稳定理论.
  • 一个线性不连续控制器的设计和实现.

主要成果:

  • 足够的条件用于固定偏差稳定.
  • 获得了足够的条件来实现固定偏差同步.
  • 通过两个模拟示例来证明控制器的有效性.

结论:

  • 提出的方法有效地实现了固定偏差稳定和同步.
关键词:
不连续的控制不连续的控制.固定偏差动态的动态分数级的复杂值神经网络.时间延迟 时间延迟

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  • 理论结果通过模拟示例来验证.
  • 这项研究有助于控制复杂的小数序神经网络.