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相关概念视频

One-Degree-of-Freedom System01:24

One-Degree-of-Freedom System

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In mechanical engineering, one-degree-of-freedom systems form the basis of a wide range of electrical and mechanical components. Using these models, engineers can predict the behavior of various parts in a larger system, which gives them insight into how different forces interact with each other.
A one-degree-of-freedom system is defined by an independent variable that determines its state and behavior. One example of a one-degree-of-freedom system is a simple harmonic oscillator, such as a...
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Pole and System Stability01:24

Pole and System Stability

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The transfer function is a fundamental concept representing the ratio of two polynomials. The numerator and denominator encapsulate the system's dynamics. The zeros and poles of this transfer function are critical in determining the system's behavior and stability.
Simple poles are unique roots of the denominator polynomial. Each simple pole corresponds to a distinct solution to the system's characteristic equation, typically resulting in exponential decay terms in the system's...
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Rigid Body Equilibrium Problems - II01:21

Rigid Body Equilibrium Problems - II

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A rigid body is in static equilibrium when the net force and the net torque acting on the system are equal to zero.
Consider two children sitting on a seesaw, which has negligible mass. The first child has a mass (m1) of 26 kg and sits at point A, which is 1.6 meters (r1) from the pivot point B; the second child has a mass (m2) of 32 kg and sits at point C. How far from the pivot point B should the second child sit (r2) to balance the seesaw?
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Time-Domain Interpretation of PD Control01:07

Time-Domain Interpretation of PD Control

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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...
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Rigid Body Equilibrium Problems - I00:49

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A rigid body is said to be in static equilibrium when the net force and the net torque acting on the system is equal to zero. To solve for rigid body equilibrium problems, do the following steps.
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Feedback control systems01:26

Feedback control systems

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Feedback control systems are categorized in various ways based on their design, analysis, and signal types.
Linear feedback systems are theoretical models that simplify analysis and design. These systems operate under the principle that their output is directly proportional to their input within certain ranges. For instance, an amplifier in a control system behaves linearly as long as the input signal remains within a specific range. However, most physical systems exhibit inherent nonlinearity...
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相关实验视频

Updated: May 20, 2025

Oscillation and Reaction Board Techniques for Estimating Inertial Properties of a Below-knee Prosthesis
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一个强大的干扰拒绝全身控制框架,用于双脚机器人使用基于动量的观察者.

Shuai Heng1, Xizhe Zang1, Yan Liu1

  • 1State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150080, China.

Biomimetics (Basel, Switzerland)
|March 26, 2025
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概括
此摘要是机器生成的。

这项研究介绍了一种强大的规划器和控制器用于双脚机器人,改善了对干扰的步行稳定性. 它使用模型预测控制 (MPC) 和基于动量的观察器,消除了对足部传感器来估计外部力的需求.

关键词:
这是一个双脚机器人.运动的分离组成部分.基于动量的观察者.整个身体的控制控制.

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科学领域:

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

背景情况:

  • 双脚机器人需要强大的控制策略来保持移动时的稳定性.
  • 外部干扰对双脚机器人的性能和安全构成重大挑战.
  • 目前的方法通常依赖于脚上安装的传感器来估计干扰,这限制了它们的适用性.

研究的目的:

  • 为双脚机器人开发一个全面的计划器和控制器方案.
  • 为了增强对外部干扰的强度,而不需要依赖脚上安装的传感器.
  • 提高地面反应力估计和干扰补偿的准确性.

主要方法:

  • 使用模型预测控制 (MPC) 的高层规划优化了根据运动的分离元件 (DCM) 优化了立足点位置和步骤持续时间.
  • 低级控制采用基于动量的观察员来估计对立场和摇摆腿的外部力量.
  • 将全身动力学和估计的干扰整合到加权全身控制 (WBC) 中,以准确计算地面反应力.

主要成果:

  • 证明了对抗外部干扰的增强步行强度.
  • 在没有脚部安装传感器的情况下,成功估计了外部力量.
  • 通过对BRUCE机器人的模拟和实验,验证了控制器在减轻干扰效应方面的有效性.

结论:

  • 拟议的计划器和控制器方案显著提高了双脚机器人对外部干扰的强度.
  • 该方法提供了一种独立于传感器的方法来估计和补偿干扰.
  • 实验验证证证实了框架在各种具有挑战性的场景中的有效性.