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相关概念视频

Open and closed-loop control systems01:17

Open and closed-loop control systems

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Control systems are foundational elements in automation and engineering. They are broadly categorized into open-loop and closed-loop systems. These classifications hinge on the presence or absence of feedback mechanisms, significantly influencing the system's performance, complexity, and application.
An open-loop control system operates without feedback from the output. It consists of two primary elements: the controller and the controlled process. The controller receives an input signal...
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Multi-input and Multi-variable systems01:22

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Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
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Parameters Affecting Nonlinear Elimination: Zero-Order Input, First-Order Absorption and Two-Compartment Model01:13

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Drugs administered through various routes can lead to nonlinear elimination, resulting in complex pharmacokinetic behaviors crucial to understanding efficacious drug dosing.
When a drug is administered through a constant intravenous infusion and eliminated via nonlinear pharmacokinetics, it follows zero-order input. For example, oral drugs undergo first-order absorption upon administration and are eliminated through nonlinear pharmacokinetics.
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Design Example: Frog Muscle Response01:14

Design Example: Frog Muscle Response

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A student is tasked to work on an intriguing experiment involving an RL (Resistor-Inductor) circuit to study the muscle response of a frog's leg to electrical stimulation. The RL circuit plays a crucial role in this experiment, providing the means to control and measure the electrical impulses that trigger muscle contraction.
When the switch connecting the RL circuit is closed, a brief muscle contraction is observed. This is because, at a steady state, the inductor acts like a short...
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Control System Problem01:21

Control System Problem

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In an open-loop system, such as a basic thermostat, the poles of the transfer function influence the system's response but do not determine its stability. However, when feedback is introduced to form a closed-loop system, such as an advanced thermostat that adjusts heating based on room temperature, stability is governed by the new poles of the closed-loop transfer function.
When forming a closed-loop system, issues can arise if the poles cross into the unstable region, leading to potential...
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Second Order systems I

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A servo system exemplifies a second-order system, featuring a proportional controller and load elements that ensure the output position aligns with the input position. The relationship between these components is described by a second-order differential equation. Applying the Laplace transform under zero initial conditions yields the transfer function, showing how inputs are converted to outputs in the system.
By reinterpreting the system, one can derive the closed-loop transfer function, which...
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Robotic Mirror Therapy System for Functional Recovery of Hemiplegic Arms
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上肢多输出多输入闭环模型的反参数.

Ian Syndergaard1, Daniel B Free1, Dario Farina2

  • 1Mechanical Engineering, Brigham Young University, Provo, Utah, United States of America.

PLoS computational biology
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概括
此摘要是机器生成的。

本研究提出了一种方法和参数估计,用于创建闭环,多输入多输出 (MIMO) 上肢神经肌肉骨模型. 这些模型对于理解运动控制和模拟四肢运动至关重要.

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科学领域:

  • 神经科学是一个神经科学.
  • 生物力学 生物力学
  • 系统生物学 系统生物学

背景情况:

  • 闭环和多输入多输出 (MIMO) 模型对于模拟上肢运动控制至关重要.
  • 现有的模型缺乏全面的,大规模的线性神经肌肉骨表示,既是闭环的,也是MIMO的.
  • 开发此类模型的一个重要障碍是缺乏已确定的反参数值 (收益和延迟).

研究的目的:

  • 引入一种方法来构建MIMO模型的短环 afferent反在上肢.
  • 根据现有文献提供反参数的估计平均值和范围.

主要方法:

  • 来自26项先前研究的综合反参数数据.
  • 应用了系统稳定性和行为原理来改进参数估计.
  • 开发了一种线性模型,包含13个表面肌肉和7个关节自由度 (从肩到手腕).
  • 包括同名反 (戈尔吉器官) 和同名/异名反 (肌肉).

主要成果:

  • 对上肢神经肌肉骨模型的估计反收益和延迟.
  • 通过比较已知中枢延迟差异的信号来验证肌肉的反收益.
  • 通过将估计的延迟与测量的内腔长度进行比较,验证了延迟时间,显示出强度适合以弗伦 (R=0.88) 和中度适合以弗伦 (R=0.65) 的延迟.
  • 证明了反对模型行为的影响,并将其与实验观测进行了比较.

结论:

  • 成功开发了一种创建MIMO神经肌肉骨模型的方法,该模型具有估计的反参数.
  • 该模型为模拟上肢运动控制提供了一个基础,使用现实的反机制来模拟上肢运动控制.
  • 这些发现有助于更好地了解神经反如何影响上肢生物力学和运动.