Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Feedback control systems01:26

Feedback control systems

541
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...
541
Control Systems01:10

Control Systems

1.6K
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...
1.6K
PD Controller: Design01:26

PD Controller: Design

435
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,...
435
Open and closed-loop control systems01:17

Open and closed-loop control systems

1.3K
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...
1.3K
Controller Configurations01:22

Controller Configurations

212
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...
212
Time-Domain Interpretation of PD Control01:07

Time-Domain Interpretation of PD Control

220
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...
220

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Low-molecular-weight polysaccharide and polyol impregnation enhances the rehydration recovery capacity of freeze-dried potato slices.

Food chemistry: X·2026
Same author

Application of Cerium-Tannic Acid-Formaldehyde Coordination Polymer Colloidal Nanomaterials to Alleviate Lipopolysaccharide-Induced Acute Lung Injury.

International journal of nanomedicine·2026
Same author

Harnessing MDM2-Mediated Targeted Degradation of Transcriptional and Epigenetic Machinery to Disrupt Oncogenic Addictions in Pediatric Sarcoma.

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

An explainable prognostic prediction panel for sepsis based on serum amino acid profiles.

Frontiers in immunology·2026
Same author

Methane inhalation during ex vivo lung perfusion protects donor lungs after cardiac death via modulation of MAPK-related inflammatory and oxidative pathways.

The Journal of heart and lung transplantation : the official publication of the International Society for Heart Transplantation·2026
Same author

IL-6 receptor blockade impedes proinflammatory atypical Treg subset associated with immune checkpoint inhibitor-induced inflammatory arthritis.

The Journal of clinical investigation·2026
Same journal

Hidden Data Recovery and Forecasting via Next-Generation Reservoir Computing With Multiscale Delay Selection.

IEEE transactions on neural networks and learning systems·2026
Same journal

CAFF-CIL: Causality-Aware Freedom Forgetting Approach for Class-Incremental Learning.

IEEE transactions on neural networks and learning systems·2026
Same journal

Harmonic Autoencoding Framework for Multiple Tasks in Magnetic Particle Imaging Reconstruction.

IEEE transactions on neural networks and learning systems·2026
Same journal

A Survey on Human-Centric Voice-Face Multimodal Learning.

IEEE transactions on neural networks and learning systems·2026
Same journal

Vision-Assisted Foundation Model for Solving Multitask Vehicle Routing Problems.

IEEE transactions on neural networks and learning systems·2026
Same journal

FP3O: Enabling Proximal Policy Optimization in Multiagent Cooperation With Parameter-Sharing Versatility.

IEEE transactions on neural networks and learning systems·2026
See all related articles

Related Experiment Video

Updated: Nov 8, 2025

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

11.9K

Design and Analysis of Data-Driven Learning Control: An Optimization-Based Approach.

Deyuan Meng, Jingyao Zhang

    IEEE Transactions on Neural Networks and Learning Systems
    |April 20, 2021
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces an optimization-based approach for data-driven learning control systems, enabling perfect tracking in repetitive systems using only input-output data. Adaptive strategies ensure convergence and boundedness without needing explicit system models.

    More Related Videos

    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

    2.7K
    Eye-tracking Technology and Data-mining Techniques used for a Behavioral Analysis of Adults engaged in Learning Processes
    10:43

    Eye-tracking Technology and Data-mining Techniques used for a Behavioral Analysis of Adults engaged in Learning Processes

    Published on: June 10, 2021

    5.6K

    Related Experiment Videos

    Last Updated: Nov 8, 2025

    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

    11.9K
    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

    2.7K
    Eye-tracking Technology and Data-mining Techniques used for a Behavioral Analysis of Adults engaged in Learning Processes
    10:43

    Eye-tracking Technology and Data-mining Techniques used for a Behavioral Analysis of Adults engaged in Learning Processes

    Published on: June 10, 2021

    5.6K

    Area of Science:

    • Control Systems Engineering
    • Machine Learning
    • Nonlinear Dynamics

    Background:

    • Repetitive systems require precise tracking for optimal performance.
    • Existing control methods often rely on accurate system models, which are difficult to obtain for nonlinear, time-varying dynamics.

    Purpose of the Study:

    • To develop an optimization-based design and analysis framework for data-driven learning control.
    • To achieve perfect output tracking in repetitive systems with unknown nonlinear dynamics using Iterative Learning Control (ILC).

    Main Methods:

    • Leveraging only measured input-output data, without explicit model knowledge.
    • Employing adaptive updating strategies for parameter estimation of system nonlinearities.
    • Utilizing a double-dynamics analysis approach and properties of nonnegative matrices to ensure convergence and boundedness.

    Main Results:

    • Demonstrated that perfect output tracking is achievable through iterative input updates.
    • Established convergence of the ILC, along with boundedness of system input, output, and estimated parameters.
    • Validated the proposed optimization-based adaptive ILC through simulations.

    Conclusions:

    • The proposed data-driven, optimization-based Iterative Learning Control effectively achieves perfect tracking in complex repetitive systems.
    • Adaptive parameter estimation and rigorous analysis ensure robust performance and stability without prior system modeling.
    • This approach offers a powerful tool for controller design in systems with unknown nonlinear dynamics.