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

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

45
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
45
Feedback control systems01:26

Feedback control systems

297
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...
297
Control Systems01:10

Control Systems

1.1K
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...
1.1K
Open and closed-loop control systems01:17

Open and closed-loop control systems

698
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...
698
Load-frequency control01:28

Load-frequency control

140
Load-frequency control (LFC) is vital for maintaining power system stability, ensuring that frequency and power flows remain within acceptable limits during load changes. Turbine-governor control eliminates rotor accelerations and decelerations following load changes. However, a steady-state frequency error persists when the change in the turbine-governor reference setting is zero. In an interconnected power system, each area agrees to export or import a scheduled amount of power through...
140
Controller Configurations01:22

Controller Configurations

90
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...
90

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

Retraction Note: A hybrid LSTM random forest model with grey wolf optimization for enhanced detection of multiple bearing faults.

Scientific reports·2026
Same author

RETRACTED: Srivastava et al. Match-Level Fusion of Finger-Knuckle Print and Iris for Human Identity Validation Using Neuro-Fuzzy Classifier. <i>Sensors</i> 2022, <i>22</i>, 3620.

Sensors (Basel, Switzerland)·2026
Same author

Leader follower second order voltage control with disturbance observer for DC microgrids.

Scientific reports·2026
Same author

Load frequency control of a PV-DSTS integrated thermal-hydro power system using a CCSA-optimized fuzzy fractional-order parallel controller.

Scientific reports·2026
Same author

CNN-based compensation of faulty planar phased-array radiation patterns.

Scientific reports·2026
Same author

Retraction Note: Enhancing residential energy access with optimized stand-alone hybrid solar-diesel-battery systems in Buea, Cameroon.

Scientific reports·2026

相关实验视频

Updated: Jun 17, 2025

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
06:45

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

Published on: October 28, 2022

1.6K

基于Lyapunov的神经网络模型的预测控制,使用元启发式优化方法.

Chafea Stiti1, Mohamed Benrabah2, Abdelhadi Aouaichia1

  • 1Laboratory of Electrical Systems and Remote Control, Blida1 University Blida, Ouled Yaïch, Algeria.

Scientific reports
|August 13, 2024
PubMed
概括

一种新的基于Lyapunov的神经网络模型预测控制方法增强了对非线性系统的控制. 这种方法确保了稳定性,并在电机控制应用中展示了卓越的准确性和速度.

关键词:
限制 限制 限制DTBO DTBO 在线播放莱帕努诺夫函数是一个函数.这是一种元启发式 (metaheuristic) 启发式.模型预测控制模型预测控制神经网络的神经网络非线性系统是非线性系统.松鼠的感应电机引擎

更多相关视频

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

11.6K
Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
11:18

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

Published on: March 2, 2015

10.3K

相关实验视频

Last Updated: Jun 17, 2025

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
06:45

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

Published on: October 28, 2022

1.6K
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

11.6K
Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
11:18

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

Published on: March 2, 2015

10.3K

科学领域:

  • 控制系统工程 控制系统工程
  • 人工智能的人工智能
  • 非线性动力学是一种非线性动力学.

背景情况:

  • 控制受约束的非线性系统在实现稳定性和性能方面存在重大挑战.
  • 现有的模型预测控制 (MPC) 方法经常与复杂系统的计算复杂性和融合速度作斗争.

研究的目的:

  • 引入一种新的基于Lyapunov的神经网络模型预测控制 (NN-MPC) 策略.
  • 为了在MPC框架内利用一个元启发式优化算法来有效解决问题.
  • 为了验证控制器在管理具有快速动态的受约束非线性系统中的有效性.

主要方法:

  • 使用feedforward神经网络作为MPC框架内的预测模型.
  • 使用基于驾驶培训的优化 (DTBO) 算法来解决受约束的优化问题.
  • 将Lyapunov函数作为成本函数中的约束,以保证闭环稳定性.

主要成果:

  • 拟议的基于Lyapunov的DTBO的NN-MPC在控制三相松鼠引擎的角度转速方面表现出卓越的准确性,速度和稳定性.
  • 与其他先进的控制技术相比,包括平均绝对误差,根平均平方误差和增强百分比在内的性能指标得到了显著改善.
  • 控制器表现出高效的计算性能,以减少计算时间为准.

结论:

  • 使用DTBO开发的基于Lyapunov的NN-MPC是一种高效和高效的技术,用于控制受约束的非线性系统.
  • 神经网络的集成和元启发式优化为先进的控制系统设计提供了一个有希望的方向.
  • 控制器的稳定性和性能使其适用于需要精确和快速控制动态系统的应用.