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

Control Systems01:10

Control Systems

1.9K
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...
1.9K
Control Systems: Applications01:25

Control Systems: Applications

1.2K
Electrical engineering plays a pivotal role in our daily lives, with control systems at the heart of many applications, from home appliances to sophisticated space shuttles. Control systems manage and regulate the behavior of devices and processes, ensuring they function safely, correctly, and efficiently.
In modern vehicles, control systems manage various functions to enhance performance and safety. The steering wheel and accelerator are primary inputs in a car's control system. The...
1.2K
Feedback control systems01:26

Feedback control systems

722
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...
722
Open and closed-loop control systems01:17

Open and closed-loop control systems

1.7K
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...
1.7K
Transfer Function in Control Systems01:21

Transfer Function in Control Systems

1.6K
The transfer function is a fundamental concept in the analysis and design of linear time-invariant (LTI) systems. It offers a concise way to understand how a system responds to different inputs in the frequency domain. It serves as a bridge between the time-domain differential equations that describe system dynamics and the frequency-domain representation that facilitates easier manipulation and analysis.
To derive the transfer function, consider a general nth-order linear time-invariant...
1.6K
Nonlinear Pharmacokinetics: Causes of Nonlinearity01:22

Nonlinear Pharmacokinetics: Causes of Nonlinearity

735
Nonlinearity in drug pharmacokinetics is caused by various factors influencing how a drug is absorbed, distributed, metabolized, and excreted. Understanding these nonlinear processes is crucial for predicting drug behavior in the body and optimizing drug dosing regimens.
Nonlinear drug absorption can occur when the process is rate-limited by solubility, carrier-mediated transport systems, or saturation of the presystemic gut wall or hepatic metabolism. For instance, high doses of riboflavin...
735

You might also read

Related Articles

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

Sort by
Same author

Social Behavior Forecasts Moment-to-Moment Changes in RSA in Infants With Autism.

Developmental science·2026
Same author

Safe Optimal Control Framework for Cooperative Manipulation of Objects in Human-Robot Teams.

IEEE transactions on cybernetics·2026
Same author

Developing an Ownership Model for Experiential Learning of Social Determinants of Health for Medical Residents.

Ochsner journal·2025
Same author

Cubical and spherical directional array-based particle source detection with poisson statistics.

Scientific reports·2025
Same author

Iterative Reservoir Computing Networks for Reconstructing Irregular Time Series.

IEEE transactions on neural networks and learning systems·2025
Same author

Inferring networks of chemical reactions by curvature analysis of kinetic trajectories.

Physical chemistry chemical physics : PCCP·2025

Related Experiment Video

Updated: Feb 4, 2026

WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control
08:18

WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control

Published on: August 15, 2020

5.4K

Approximate Optimal Distributed Control of Nonlinear Interconnected Systems Using Event-Triggered Nonzero-Sum Games.

Vignesh Narayanan, Avimanyu Sahoo, Sarangapani Jagannathan

    IEEE Transactions on Neural Networks and Learning Systems
    |October 9, 2018
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces approximate optimal distributed control for nonlinear systems using event-sampled feedback. It ensures system stability and accurate control through a novel hybrid-learning scheme and neural networks.

    More Related Videos

    Author Spotlight: Unveiling the Potential of VSFG Microscopy in Studying Mesoscopically Heterogeneous Self-Assembled Structures
    08:49

    Author Spotlight: Unveiling the Potential of VSFG Microscopy in Studying Mesoscopically Heterogeneous Self-Assembled Structures

    Published on: December 1, 2023

    2.1K
    Exploring the Sequential Cellular Events of Phagocytosis Triggered by Godanti Bhasma in Mammalian Cells
    10:10

    Exploring the Sequential Cellular Events of Phagocytosis Triggered by Godanti Bhasma in Mammalian Cells

    Published on: July 11, 2025

    740

    Related Experiment Videos

    Last Updated: Feb 4, 2026

    WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control
    08:18

    WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control

    Published on: August 15, 2020

    5.4K
    Author Spotlight: Unveiling the Potential of VSFG Microscopy in Studying Mesoscopically Heterogeneous Self-Assembled Structures
    08:49

    Author Spotlight: Unveiling the Potential of VSFG Microscopy in Studying Mesoscopically Heterogeneous Self-Assembled Structures

    Published on: December 1, 2023

    2.1K
    Exploring the Sequential Cellular Events of Phagocytosis Triggered by Godanti Bhasma in Mammalian Cells
    10:10

    Exploring the Sequential Cellular Events of Phagocytosis Triggered by Godanti Bhasma in Mammalian Cells

    Published on: July 11, 2025

    740

    Area of Science:

    • Control Theory
    • Systems Engineering
    • Applied Mathematics

    Background:

    • Distributed control of nonlinear interconnected systems presents challenges due to strong interconnections.
    • Event-sampled feedback offers potential for efficient data transmission but requires careful stability analysis.

    Purpose of the Study:

    • To develop approximate optimal distributed control schemes for nonlinear interconnected systems.
    • To utilize event-sampled feedback for enhanced control efficiency and decentralized operation.
    • To ensure system stability and convergence of neural network parameters.

    Main Methods:

    • Formulating the control problem as an N-player nonzero-sum game.
    • Employing approximate dynamic programming with critic neural networks (NNs) to solve the coupled Hamilton-Jacobi equation.
    • Designing decentralized, asynchronous event-sampling conditions for state vector transmission.
    • Introducing a hybrid-learning scheme for local ultimate boundedness and Lyapunov-based stability analysis.

    Main Results:

    • An approximate Nash equilibrium solution for the game was obtained using NNs.
    • Novel decentralized event-sampling conditions were developed for asynchronous state transmission.
    • The hybrid-learning scheme ensured local ultimate boundedness of system states and NN parameter errors.
    • Zeno-free behavior of the event-sampled system was analytically proven.

    Conclusions:

    • The proposed event-based distributed control scheme effectively manages nonlinear interconnected systems.
    • The approach ensures stability and convergence using advanced dynamic programming and neural network techniques.
    • The methodology is applicable to linear interconnected systems and validated by numerical examples.