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相关概念视频

Time-Domain Interpretation of PD Control01:07

Time-Domain Interpretation of PD Control

141
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...
141
Controller Configurations01:22

Controller Configurations

119
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...
119
PD Controller: Design01:26

PD Controller: Design

282
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,...
282
PI Controller: Design01:24

PI Controller: Design

331
Proportional Integral (PI) controllers are a fundamental component in modern control systems, widely used to enhance performance and mitigate steady-state errors. They are particularly effective in applications such as automatic brightness adjustment on smartphones, where they excel at mitigating steady-state errors for step-function inputs. Unlike PD controllers, which require time-varying errors to function optimally, PI controllers leverage their integral component to address residual...
331
Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

101
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,...
101
Kinematic Equations: Problem Solving01:15

Kinematic Equations: Problem Solving

12.5K
When analyzing one-dimensional motion with constant acceleration, the problem-solving strategy involves identifying the known quantities and choosing the appropriate kinematic equations to solve for the unknowns. Either one or two kinematic equations are needed to solve for the unknowns, depending on the known and unknown quantities. Generally, the number of equations required is the same as the number of unknown quantities in the given example. Two-body pursuit problems always require two...
12.5K

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相关实验视频

Updated: Jul 20, 2025

A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study
06:58

A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study

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对操纵器进行基于双时间尺度非概率学可靠性的控制器优化,考虑到运动误差和磨损增长.

Lei Wang1, Zheng Zhou2, Jiaxiang Liu2

  • 1National Key Laboratory of Strength and Structural Integrity, Institute of Solid Mechanics, School of Aeronautic Science and Engineering, Beihang University, Beijing 100191, China; Aircraft and Propulsion Laboratory, Ningbo Institute of Technology, Beihang University, Ningbo 315100, China.

ISA transactions
|August 4, 2023
PubMed
概括

本研究引入了一种新的优化方法,通过解决运动错误和磨损增长来提高操纵器系统性能. 该方法确保了对时间依赖和时间独立因素的可靠性,改善了控制和寿命.

关键词:
适应性亚间隔合法适应性亚间隔合法双倍的时间尺度.操纵器的操纵器是什么非概率学可靠性 不可能的可靠性不统一的清算方式

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相关实验视频

Last Updated: Jul 20, 2025

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科学领域:

  • 机器人和控制系统 机器人和控制系统
  • 机械工程 机械工程
  • 可靠性工程可靠性工程

背景情况:

  • 操纵器系统的性能受到运动误差和磨损增长的严重影响,影响控制精度和操作寿命.
  • 现有的方法往往无法全面解决这些可靠性因素的多尺度时间性质.

研究的目的:

  • 为操纵器控制器提出基于双时间尺度非概率可靠性 (DTSNPR) 的优化方法.
  • 将运动误差的时间依赖可靠性 (TDR) 和磨损增长的时间独立可靠性 (TIR) 整合到一个统一的框架中.
  • 提高非线性操纵器系统不确定性传播分析的精度和效率.

主要方法:

  • 开发DTSNPR方法,同时评估和优化控制器,同时考虑运动误差和磨损增长.
  • 采用自适应子间隔拼接方法 (ASICM) 来处理高度非线性不确定性传播问题.
  • 在三个数值操纵系统上应用和验证拟议的方法.

主要成果:

  • DTSNPR方法成功地确保了操纵器系统在预定义的可靠性级别下运行,无论是运动错误还是磨损增长.
  • 与传统方法相比,ASICM在计算成本 (1%的蒙特卡洛) 和精度 (0.4%的误差) 中表现出显著的优势.
  • 综合方法为优化不同时间尺度上的操纵器可靠性提供了一个强大的框架.

结论:

  • 提出的基于DTSNPR的优化方法为评估和提高操纵器系统可靠性提供了全面的解决方案.
  • ASICM提供了一种计算效率高,准确的方法,用于分析机器人系统中的非线性不确定性传播.
  • 这项研究有助于在各种工业应用中开发更可靠,更持久的操纵系统.