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

586
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...
586
Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

234
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,...
234
Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

280
Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear....
280
Open and closed-loop control systems01:17

Open and closed-loop control systems

1.4K
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...
1.4K
PD Controller: Design01:26

PD Controller: Design

493
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,...
493
State Space Representation01:27

State Space Representation

420
The frequency-domain technique, commonly used in analyzing and designing feedback control systems, is effective for linear, time-invariant systems. However, it falls short when dealing with nonlinear, time-varying, and multiple-input multiple-output systems. The time-domain or state-space approach addresses these limitations by utilizing state variables to construct simultaneous, first-order differential equations, known as state equations, for an nth-order system.
Consider an RLC circuit, a...
420

You might also read

Related Articles

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

Sort by
Same author

Agmatine induces mitophagy via the PTS-I2R pathway to increase autophagic flux and attenuate sepsis-induced intestinal epithelial cell apoptosis.

Inflammation research : official journal of the European Histamine Research Society ... [et al.]·2026
Same author

Sex-specific responses of finishing pigs to dietary protein restriction in nutrient utilization and nitrogen-related metabolites derived from gut microbiota.

Scientific reports·2026
Same author

ADA-YOLO: An Adaptive Dynamic Aggregation Network for Small Object Detection in UAV Imagery.

Sensors (Basel, Switzerland)·2026
Same author

Multi-tissue transcriptomics reveals age-dependent susceptibility to grass carp reovirus linked to metabolic alterations and extracellular matrix disruption in grass carp.

Fish & shellfish immunology·2026
Same author

Targeting Membrane Lipid and Curvature Signatures for Neuronal Exosome Capture and Protein Profiling as a Liquid Biopsy for Cognitive Impairment.

Analytical chemistry·2026
Same author

Inverse Reinforcement Learning H <sub>∞</sub> Optimal Control for Takagi-Sugeno Fuzzy Systems.

IEEE transactions on cybernetics·2026

Related Experiment Video

Updated: Dec 6, 2025

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

10.6K

Adaptive Neural Network Finite-Time Dynamic Surface Control for Nonlinear Systems.

Kewen Li, Yongming Li

    IEEE Transactions on Neural Networks and Learning Systems
    |October 13, 2020
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a novel neural network adaptive dynamic surface control for nonlinear systems. The method ensures finite-time stability and fast tracking error convergence, outperforming existing algorithms.

    Failed At:

    2026-06-19T13:38:45.742920+00:00

    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

    Related Experiment Videos

    Last Updated: Dec 6, 2025

    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

    10.6K
    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