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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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Design Example: Creating a Hydraulic Model of a Dam Spillway01:21

Design Example: Creating a Hydraulic Model of a Dam Spillway

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Scaled hydraulic models of dam spillways provide a practical way to replicate and study the intricate flow dynamics of these structures. Often built to a 1:15 ratio, these models allow for observing critical water behavior, such as velocity distribution, flow patterns, and energy dissipation.
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Root-Locus Method01:19

Root-Locus Method

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A cruise control system in a car is designed to maintain a specified speed automatically by adjusting the gas pedal. The system continuously measures the vehicle's speed and makes fine adjustments to the pedal to achieve this goal. The root locus method is particularly useful for understanding how the cruise control system's behavior changes under varying conditions, such as when the car goes uphill, downhill, or faces strong wind resistance.
This system can be represented by a block...
456
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...
355
Feedback control systems01:26

Feedback control systems

676
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...
676
PD Controller: Design01:26

PD Controller: Design

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In automotive engineering, car suspension systems often employ Proportional Derivative (PD) controllers to enhance performance. PD controllers are utilized to adjust the damping force in response to road conditions. A controller, acting as an amplifier with a constant gain, demonstrates proportional control, with output directly mirroring input.
Designing a continuous-data controller requires selecting and linking components like adders and integrators, which are fundamental in Proportional,...
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相关实验视频

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基于未知的系统动态估计器的道控制,用于液压驱动的下肢外骨架机器人机器人.

Jinsong Zhao1, Huidong Hou2, Yunpeng Zhang2

  • 1School of Mechanical Engineering, Yanshan University, Qinhuangdao, 066004, China; Hebei Provincial Key Laboratory of Heavy Machinery Fluid Power Transmission and Control, Yanshan University, Qinhuangdao, 066004, China; Key Laboratory of Advanced Forging & Stamping Technology and Science (Yanshan University), Ministry of Education of China, Qinhuangdao, 066004, China; State Key Laboratory of Crane Technology, Yanshan University, Qinhuangdao, 066004, China.

ISA transactions
|November 19, 2025
PubMed
概括

这项研究引入了一种新的漏斗控制 (FC) 策略,使用未知的系统动态估计器 (USDE) 来改进液压驱动下肢外骨架机器人 (HDLLER) 的轨迹跟踪. 该方法有效地弥补不确定性和干扰,提高机器人的性能.

关键词:
道控制器的控制器人与机器人的合液压驱动的下肢外骨架机器人机器人未知系统动态估计器未知

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科学领域:

  • 机器人技术 机器人技术 机器人技术
  • 控制系统工程 控制系统工程
  • 生物力学 生物力学

背景情况:

  • 液压驱动的下肢外骨架机器人 (HDLLER) 增强了人类的移动性,但在精确控制方面面临着挑战.
  • 人机合和系统不确定性阻碍了准确的轨迹跟踪.

研究的目的:

  • 为HDDLLERs制定一个强大的控制策略,以解决未知的动态和外部干扰.
  • 为了提高下肢外骨架机器人的轨迹跟踪精度和整体性能.

主要方法:

  • 提出了一种与未知的系统动态估计器 (USDE) 集成的新型漏斗控制 (FC) 策略.
  • 为了管理复杂性,HDLLER动态模型被转化为布鲁诺夫斯基法典形式.
  • 高增益观察器 (HGO) 用于状态重建,修改后的漏斗函数限制了跟踪错误.

主要成果:

  • 拟议的FC-USDE战略有效地弥补了未知的内部和外部动态影响.
  • 模拟和实验表明,在轨迹跟踪中,过渡和稳定状态性能得到了改进.
  • 该方法成功地管理了高阶系统中的"复杂性爆炸".

结论:

  • 开发的漏斗控制策略与未知的系统动态估计器提供了一个强大的解决方案,用于精确的轨迹跟踪在HDLLERs.
  • 这种方法通过减轻不确定性和干扰来提高外骨机器人的性能.
  • 通过模拟和步行实验验证,该方法显示出对外骨应用的巨大潜力.