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

691
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...
691
Control System Problem01:21

Control System Problem

414
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...
414
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

412
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,...
412
Combinatorial Gene Control02:33

Combinatorial Gene Control

9.5K
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...
9.5K
Control Systems01:10

Control Systems

1.8K
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...
1.8K
Controller Configurations01:22

Controller Configurations

357
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...
357

You might also read

Related Articles

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

Sort by
Same authorSame journal

Output Tracking of Periodically Time-Varying Boolean Networks: State-Flipped Control and Q-Learning Approaches.

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

Potential impacts of delay on pinning impulsive secure synchronization control of delayed networks.

ISA transactions·2025
Same author

Learning-based minimum cost strategies for set reachability of Boolean control networks under data injection attacks.

Neural networks : the official journal of the International Neural Network Society·2025
Same author

An approach to inferring gene regulatory networks via boolean modeling and feature selection.

Neural networks : the official journal of the International Neural Network Society·2025
Same author

Impulsive Observer of Linear Systems: An Adaptive Impulsive Gain Approach.

IEEE transactions on cybernetics·2025
Same author

Global Synchronization of High-Dimensional Heterogeneous Kuramoto Oscillator Networks: Pinning Impulsive Approach.

IEEE transactions on cybernetics·2025

Related Experiment Video

Updated: Jan 21, 2026

Control of Eating Behavior Using a Novel Feedback System
04:48

Control of Eating Behavior Using a Novel Feedback System

Published on: May 8, 2018

11.5K

Output Feedback Control for Set Stabilization of Boolean Control Networks.

Rongjian Liu, Jianquan Lu, Wei Xing Zheng

    IEEE Transactions on Neural Networks and Learning Systems
    |August 13, 2019
    PubMed
    Summary

    This study introduces a new method for stabilizing Boolean control networks (BCNs) using output feedback control invariant (OFCI) subsets. The spanning tree method efficiently finds all stabilizers, reducing computational costs for BCN state feedback stabilization.

    More Related Videos

    Force and Position Control in Humans - The Role of Augmented Feedback
    06:31

    Force and Position Control in Humans - The Role of Augmented Feedback

    Published on: June 19, 2016

    8.2K
    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

    1.6K

    Related Experiment Videos

    Last Updated: Jan 21, 2026

    Control of Eating Behavior Using a Novel Feedback System
    04:48

    Control of Eating Behavior Using a Novel Feedback System

    Published on: May 8, 2018

    11.5K
    Force and Position Control in Humans - The Role of Augmented Feedback
    06:31

    Force and Position Control in Humans - The Role of Augmented Feedback

    Published on: June 19, 2016

    8.2K
    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

    1.6K

    Area of Science:

    • Systems Biology
    • Control Theory
    • Computational Biology

    Background:

    • Boolean control networks (BCNs) are widely used to model complex biological systems.
    • Stabilization is a key challenge in controlling BCNs, especially with output feedback.
    • Existing methods for designing stabilizers can be computationally intensive.

    Purpose of the Study:

    • To investigate the output feedback set stabilization problem for BCNs.
    • To introduce and develop methods for identifying output feedback control invariant (OFCI) subsets.
    • To present a novel technique for calculating all possible output feedback set stabilizers.

    Main Methods:

    • Utilizing the semi-tensor product (STP) tool for BCN analysis.
    • Introducing the concept of output feedback control invariant (OFCI) subsets.
    • Developing a spanning tree method to compute output feedback set stabilizers.

    Main Results:

    • Novel methods for obtaining OFCI subsets are presented.
    • The spanning tree method effectively calculates all possible output feedback set stabilizers.
    • The proposed technique demonstrates reduced computational cost compared to existing methods for BCN state feedback stabilization.

    Conclusions:

    • The developed methods provide an efficient approach to output feedback set stabilization in BCNs.
    • The spanning tree method is applicable to both output and state feedback stabilization problems.
    • This work offers significant improvements in computational efficiency for BCN control design.