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

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
One-Degree-of-Freedom System01:24

One-Degree-of-Freedom System

640
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...
640
Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

199
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,...
199
Feedback control systems01:26

Feedback control systems

556
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...
556
Second Order systems I01:20

Second Order systems I

350
A servo system exemplifies a second-order system, featuring a proportional controller and load elements that ensure the output position aligns with the input position. The relationship between these components is described by a second-order differential equation. Applying the Laplace transform under zero initial conditions yields the transfer function, showing how inputs are converted to outputs in the system.
By reinterpreting the system, one can derive the closed-loop transfer function, which...
350
Controller Configurations01:22

Controller Configurations

222
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...
222

You might also read

Related Articles

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

Sort by
Same author

Vehicle Detection in Drone Aerial Views Based on Lightweight YOLOv10-IAD.

Sensors (Basel, Switzerland)·2026
Same author

Euphorbia humifusa Willd. alleviates ulcerative colitis by inhibiting lipid peroxidation via ACSL4/COX-2 axis.

Journal of ethnopharmacology·2026
Same author

Association of physical component score with high-risk lung nodules among Chinese Urban sanitation workers: a sex-specific analysis.

Frontiers in public health·2026
Same author

CYP2C19 as a key enzyme in the metabolism of cantharidin in Huh-7 cells and mice.

Archives of toxicology·2026
Same author

The Association of EGFL7 Polymorphism and Expression with Cervical Cancer Susceptibility and Pathogenesis.

International journal of general medicine·2026
Same author

Association of EGFR and EGF gene polymorphisms with cervical cancer in a case-control study and cross-cancer meta-analysis.

Scientific reports·2026
Same journal

Research on a Regional Availability Evaluation Model for Road-Area High-Entropy Energy Based on Synergy Factors.

Entropy (Basel, Switzerland)·2026
Same journal

Atmospheric Turbulence Channel Modeling and Performance Analysis of a CO-ZP-OFDM Coherent Optical Communication System for UAV Air-to-Ground Scenarios.

Entropy (Basel, Switzerland)·2026
Same journal

Information Geometry and Asymptotic Theory for SMML Estimators.

Entropy (Basel, Switzerland)·2026
Same journal

Correlation Entropy and Power-Law Kinetics.

Entropy (Basel, Switzerland)·2026
Same journal

Research on the Contagion of Systemic Financial Risk Under the Impact of Climate Risks-From the Perspective of Complex Networks and Machine Learning.

Entropy (Basel, Switzerland)·2026
Same journal

The Statistical-Mechanical Meaning of the Wave Function of Quantum Mechanics.

Entropy (Basel, Switzerland)·2026
See all related articles

Related Experiment Video

Updated: Nov 17, 2025

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

2.8K

U-Model-Based Two-Degree-of-Freedom Internal Model Control of Nonlinear Dynamic Systems.

Ruobing Li1, Quanmin Zhu1, Pritesh Narayan1

  • 1Department of Engineering Design and Mathematics, University of the West of England, Frenchay Campus, Coldharbour Lane, Bristol BS16 1QY, UK.

Entropy (Basel, Switzerland)
|February 12, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces a U-Model-Based Two-Degree-of-Freedom Internal Model Control (UTDF-IMC) for nonlinear systems. This advanced control method enhances performance by separating tracking and robustness, effectively managing model errors and disturbances.

Keywords:
Internal Model Control (IMC)Two-Degree-of-Freedom IMC (TDF-IMC)U-modelU-model-based Control (U-control)dynamic inversioninvariance entropy

More Related Videos

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

2.0K
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

12.0K

Related Experiment Videos

Last Updated: Nov 17, 2025

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

2.8K
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

2.0K
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

12.0K

Area of Science:

  • Control Systems Engineering
  • Nonlinear Dynamics
  • Process Control

Background:

  • Traditional control methods often rely on linearization, which can limit performance for complex nonlinear systems.
  • Existing Internal Model Control (IMC) structures may struggle with significant modeling errors and external disturbances.
  • There is a need for robust control strategies that can handle nonlinear dynamics without simplification.

Purpose of the Study:

  • To propose and analyze a novel U-Model-Based Two-Degree-of-Freedom Internal Model Control (UTDF-IMC) structure.
  • To demonstrate the UTDF-IMC's capability in nonlinear dynamic inversion and separation of tracking/robustness design.
  • To validate the effectiveness of the UTDF-IMC for both linear and nonlinear plants, including industrial applications.

Main Methods:

  • Development of a U-Model-Based Two-Degree-of-Freedom Internal Model Control (UTDF-IMC) framework.
  • Analysis of key properties related to tracking design and robustness against modeling errors and disturbances.
  • Computational experiments using MATLAB/Simulink for benchmark testing on linear and nonlinear plants.
  • Simulation of IMC for a Permanent Magnet Synchronous Motor (PMSM) to assess industrial applicability.

Main Results:

  • The proposed UTDF-IMC effectively handles nonlinear dynamics and accommodates modeling errors and disturbances.
  • Separation of tracking and robustness design allows for improved control performance.
  • Benchmark tests on linear and nonlinear plants confirm the method's efficacy.
  • Simulations on a PMSM demonstrate the practical potential for industrial systems.

Conclusions:

  • The UTDF-IMC offers a robust and effective approach for controlling nonlinear systems.
  • This method overcomes limitations of linearization techniques in control design.
  • The UTDF-IMC shows significant promise for real-world industrial control applications.