Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Control Systems01:10

Control Systems

1.8K
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...
1.8K
Time-Domain Interpretation of PD Control01:07

Time-Domain Interpretation of PD Control

358
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...
358
PD Controller: Design01:26

PD Controller: Design

604
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,...
604
Feedback control systems01:26

Feedback control systems

684
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...
684
PI Controller: Design01:24

PI Controller: Design

1.1K
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...
1.1K
Controller Configurations01:22

Controller Configurations

345
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...
345

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

"Alkaline-Hammer Strategy" Breaks Acidic and Stromal Barriers to Induce Alkaliptosis and Enhance Immunotherapy in Pancreatic Cancer.

Angewandte Chemie (International ed. in English)·2026
Same author

Elevated glucose-to-platelet ratio predicts short- term and long-term mortality in critically ill patients with acute ischemic stroke.

Scientific reports·2026
Same author

Enhancing interpretable soft sensing with embedded hybrid modeling: the GraphTrans approach for industrial processes.

ISA transactions·2026
Same author

Differential distribution of microplastics in breast cancer and peritumoral tissues and relationship with clinical characteristics.

Apoptosis : an international journal on programmed cell death·2026
Same author

Tumour-infiltrating adipocyte-derived 12,13-DiHOME subverts CD8<sup>+</sup> T cell immunity in pancreatic ductal adenocarcinoma by promoting PPARγ-mediated ferritinophagy and tumour-associated neutrophil ferroptosis.

Gut·2026
Same author

Gut Microbiota Regulates Systemic Inflammatory Response and Compensatory Anti-Inflammatory Response Syndromes by Targeting PF4<sup>+</sup> Macrophages in Acute Pancreatitis.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026

相关实验视频

Updated: Jan 12, 2026

Interactive and Visualized Online Experimentation System for Engineering Education and Research
08:35

Interactive and Visualized Online Experimentation System for Engineering Education and Research

Published on: November 24, 2021

2.9K

一种强大的强化学习控制方法,用于不确定的工艺工业,基于知识限制的对抗性扰乱.

Tianhao Liu, Can Zhou, Yonggang Li

    IEEE transactions on cybernetics
    |November 4, 2025
    PubMed
    概括

    本研究介绍了一种强化学习 (RL) 方法,用于在不确定的条件下优化过程控制. 该方法通过模拟干扰来提高可靠性,改善工业过程指标管理.

    科学领域:

    • 化学工程是化学工程的重要组成部分.
    • 控制系统工程 控制系统工程
    • 人工智能的人工智能

    背景情况:

    • 由于资源和能源的限制,加工行业面临着优化连续制造的挑战.
    • 强化学习 (RL) 显示出对控制的希望,但受到影响可靠性的不确定的干扰的阻碍.
    • 现有的方法难以准确地建模和减轻复杂工业过程中的干扰.

    研究的目的:

    • 开发一种强化学习 (RRL) 控制方法,用于在不确定的环境中优化过程指标.
    • 解决固有和外部不确定性对工业过程控制可靠性的影响.
    • 为了提高过程工业中控制策略的性能,尽管有不可预测的干扰.

    主要方法:

    • 为强大的RL (RRL) 提出了一个知识受约束的对抗性扰动方法.
    • 开发了一个反应大气指标替代模型来量化固有的不确定性.
    • 引入了一个动态状态扰动集与更新策略和外部不确定的时间序列生成方法.

    主要成果:

    • RRL方法有效地通过扰乱观察到的状态来表征不确定的干扰.
    • 替代模型量化了固有的不确定性,动态扰动确保了理性.
    • 在电的案例验证表明,在不确定性条件下,控制性能得到了提高.

    更多相关视频

    Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control
    05:47

    Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control

    Published on: August 29, 2025

    410
    The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
    11:53

    The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

    Published on: October 14, 2017

    12.1K

    相关实验视频

    Last Updated: Jan 12, 2026

    Interactive and Visualized Online Experimentation System for Engineering Education and Research
    08:35

    Interactive and Visualized Online Experimentation System for Engineering Education and Research

    Published on: November 24, 2021

    2.9K
    Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control
    05:47

    Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control

    Published on: August 29, 2025

    410
    The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
    11:53

    The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

    Published on: October 14, 2017

    12.1K

    结论:

    • 拟议的知识受限对抗扰乱RRL方法在不确定的工业场景中显著提高了控制可靠性.
    • 复合建模和替代模型对于处理过程不确定性是有效的.
    • 该方法为优化连续制造工艺的可行解决方案提供了可行的解决方案,并提高了稳定性.