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相关概念视频

Control Systems01:10

Control Systems

959
Control systems are everywhere in contemporary society, influencing diverse applications from aerospace to automated manufacturing. These systems can be found naturally within biological processes, such as blood sugar regulation and heart rate adjustment in response to stress, as well as in man-made systems like elevators and automated vehicles. A control system is essentially a network of subsystems and processes that collaboratively convert specific inputs into desired outputs.
At the heart...
959
Time-Domain Interpretation of PD Control01:07

Time-Domain Interpretation of PD Control

66
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...
66
Controller Configurations01:22

Controller Configurations

70
Controller configurations are crucial in a car's cruise control system because they manage speed over time to maintain a consistent pace regardless of road conditions, thereby meeting design goals. In traditional control systems, fixed-configuration design involves predetermined controller placement. System performance modifications are known as compensation.
Control-system compensation involves various configurations, most commonly series or cascade compensation, in which the controller...
70
One-Degree-of-Freedom System01:24

One-Degree-of-Freedom System

435
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...
435
PD Controller: Design01:26

PD Controller: Design

140
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,...
140
Feedback control systems01:26

Feedback control systems

252
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...
252

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The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
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德尔塔机器人的智能容错控制:用于增强轨迹跟踪的混合优化方法.

Carlos Domínguez1, Claudio Urrea1

  • 1Electrical Engineering Department, Faculty of Engineering, University of Santiago of Chile (USACH), Las Sophoras 165, Estación Central, Santiago 9170124, Chile.

Sensors (Basel, Switzerland)
|April 28, 2025
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概括

本研究介绍了Delta型机器人的主动故障耐受控制 (AFTC),以提高故障下的性能. 该系统实现了完美的故障诊断,并减少了性能退化,提高了机器人系统的可靠性.

关键词:
活跃的耐故障控制器机器人是三角洲机器人错误诊断 错误诊断 错误诊断 是一个问题.遗传算法 遗传算法梯度下降的降落方式混合优化 混合优化线性分辨器的线性分辨器这就是meta-learning.主要组件分析的主要组件分析波纹散射网络是一种波纹散射网络.

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科学领域:

  • 机器人和控制系统 机器人和控制系统
  • 故障诊断和耐受性控制
  • 并行操纵器 并行操纵器

背景情况:

  • 德尔塔型机器人表现出动力学复杂性和多驱动器依赖性,使它们容易因故障而降低性能.
  • 现有的耐故障控制方法可能无法充分解决Delta型并行机器人的复杂故障场景.

研究的目的:

  • 为Delta型平行机器人开发一种新的主动故障耐受控制 (AFTC) 策略.
  • 将先进的故障诊断系统与强大的控制策略相结合,以减轻性能退化.
  • 在故障条件下提高复杂机器人系统的轨迹跟踪精度.

主要方法:

  • 使用混合特征提取算法的故障诊断系统,该算法结合了波形散射网络 (WSN),主要组件分析 (PCA),线性差异分析 (LDA) 和元学习 (ML).
  • 一个混合优化框架,集成遗传算法和梯度下降来重新配置Type-2模糊控制器以实现容错控制.
  • 实时识别和分类单元和多元组件故障 (执行器,传感器).

主要成果:

  • 故障诊断系统在四个分类器实现了完美的准确性.
  • 建议的AFTC方法有效地将关键性能退化降低到中等水平,即使在多个故障的情况下.
  • 重新配置的Type-2模糊控制器在保持机器人的性能方面表现出了强性.

结论:

  • 开发的AFTC战略对于Delta型平行机器人来说是强大而高效的.
  • 集成故障诊断和控制系统显著提高了故障条件下的可靠性和性能.
  • 这种方法有可能提高复杂的机器人系统的轨迹跟踪精度,这些系统面临不利的操作条件.