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 System Problem01:21

Control System Problem

437
In an open-loop system, such as a basic thermostat, the poles of the transfer function influence the system's response but do not determine its stability. However, when feedback is introduced to form a closed-loop system, such as an advanced thermostat that adjusts heating based on room temperature, stability is governed by the new poles of the closed-loop transfer function.
When forming a closed-loop system, issues can arise if the poles cross into the unstable region, leading to potential...
437
Combinatorial Gene Control02:33

Combinatorial Gene Control

9.7K
Combinatorial gene control is the synergistic action of several transcriptional factors to regulate the expression of a single gene. The absence of one or more of these factors may lead to a significant difference in the level of gene expression or repression.
The expression of more than 30,000 genes is controlled by approximately 2000-3000 transcription factors. This is possible because a single transcription factor can recognize more than one regulatory sequence. The specificity in gene...
9.7K
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

473
Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
473
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
Controller Configurations01:22

Controller Configurations

380
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...
380
PID Controller01:19

PID Controller

719
Proportional-Integral-Derivative (PID) controllers are widely used in various control systems to enhance stability and performance. In a thermostat, it adjusts heating or cooling based on the temperature difference between the actual and desired levels. They are often used in automotive speed systems, effectively managing sudden speed changes while maintaining a constant speed under varying conditions. On the other hand, PI controllers, commonly employed in voltage regulation, enhance stability...
719

You might also read

Related Articles

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

Sort by
Same authorSame journal

Adaptive Global Asymptotic Output Stabilization of Uncertain Nonlinear Systems Under Dynamic State/Input Quantization.

IEEE transactions on cybernetics·2026
Same author

CDK9 degrader induces BRCAness and sensitizes castration-resistant prostate cancer to PARP inhibitor.

Theranostics·2026
Same author

Without Paired Labeled Data: End-to-End Self-Supervised Learning for Drone-View Geo-Localization.

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

Diffusion Graph Transformer for Learning Controllability Robustness in Large-Scale Networks.

IEEE transactions on cybernetics·2026
Same author

Functionalized polymeric nanomaterials for BMP-2 delivery: recent advances toward improved bone regeneration.

Nanomedicine (London, England)·2026
Same author

Brain-Controlled Wheeled Mobile Robots: A Shared Control Framework Integrating Event-Triggered Mechanism and Deep Reinforcement Learning.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society·2026

Related Experiment Video

Updated: Feb 4, 2026

Author Spotlight: Enhancing Engineering Education via WebVR-Based Online Laboratories
04:15

Author Spotlight: Enhancing Engineering Education via WebVR-Based Online Laboratories

Published on: February 23, 2024

1.7K

Minimum Cost Control of Directed Networks With Selectable Control Inputs.

Guoqi Li, Jie Ding, Changyun Wen

    IEEE Transactions on Cybernetics
    |October 2, 2018
    PubMed
    Summary

    This study introduces a new method for minimum cost control in complex networks, optimizing system performance by selecting control inputs and minimizing energy expenditure. The research identifies key network nodes crucial for reducing average control costs.

    More Related Videos

    Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator
    06:04

    Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator

    Published on: February 14, 2025

    1.1K
    Low-Cost, Volume-Controlled Dipstick Urinalysis for Home-Testing
    06:55

    Low-Cost, Volume-Controlled Dipstick Urinalysis for Home-Testing

    Published on: May 8, 2021

    6.3K

    Related Experiment Videos

    Last Updated: Feb 4, 2026

    Author Spotlight: Enhancing Engineering Education via WebVR-Based Online Laboratories
    04:15

    Author Spotlight: Enhancing Engineering Education via WebVR-Based Online Laboratories

    Published on: February 23, 2024

    1.7K
    Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator
    06:04

    Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator

    Published on: February 14, 2025

    1.1K
    Low-Cost, Volume-Controlled Dipstick Urinalysis for Home-Testing
    06:55

    Low-Cost, Volume-Controlled Dipstick Urinalysis for Home-Testing

    Published on: May 8, 2021

    6.3K

    Area of Science:

    • Control Theory
    • Network Science
    • Optimization

    Background:

    • Minimum cost control is critical for complex networks.
    • Existing methods often lack input selection flexibility.
    • Energy efficiency in network control is a growing concern.

    Purpose of the Study:

    • To address the minimum cost control problem with selectable inputs.
    • To develop an iterative algorithm for determining the optimal input matrix.
    • To gain insights into node importance for cost minimization in directed networks.

    Main Methods:

    • An orthonormal-constraint-based projected gradient method is proposed.
    • The cost function incorporates quadratic terms of system input and state with a weighting factor.
    • Iterative determination of the input matrix is employed.

    Main Results:

    • Convergence of the proposed algorithm is mathematically established.
    • Extensive simulations demonstrate the algorithm's effectiveness.
    • Node importance for minimizing average control cost in various network structures was investigated.

    Conclusions:

    • The developed method provides an effective approach to minimum cost control with selectable inputs.
    • The study offers valuable physical insights into energy-efficient control of directed networks.
    • Identifying critical nodes can significantly reduce control costs.