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

Pole and System Stability01:24

Pole and System Stability

527
The transfer function is a fundamental concept representing the ratio of two polynomials. The numerator and denominator encapsulate the system's dynamics. The zeros and poles of this transfer function are critical in determining the system's behavior and stability.
Simple poles are unique roots of the denominator polynomial. Each simple pole corresponds to a distinct solution to the system's characteristic equation, typically resulting in exponential decay terms in the system's...
527
BIBO stability of continuous and discrete -time systems01:24

BIBO stability of continuous and discrete -time systems

608
System stability is a fundamental concept in signal processing, often assessed using convolution. For a system to be considered bounded-input bounded-output (BIBO) stable, any bounded input signal must produce a bounded output signal. A bounded input signal is one where the modulus does not exceed a certain constant at any point in time.
To determine the BIBO stability, the convolution integral is utilized when a bounded continuous-time input is applied to a Linear Time-Invariant (LTI) system....
608
Stability of structures01:14

Stability of structures

286
In mechanical engineering, the stability of systems under various forces is critical for designing durable and efficient structures. One fundamental way to explore these concepts is by analyzing systems like two rods connected at a pivot point, O, with a torsional spring of spring constant k at the pivot point. This system is similar in appearance to a scissor jack used to change tires on a car. In this case, the arms of the linkage (equivalent to the rods in this system) are entirely vertical,...
286
Time and frequency -Domain Interpretation of PI Control01:27

Time and frequency -Domain Interpretation of PI Control

234
Proportional-Integral (PI) controllers are essential in many control systems to improve stability and performance. They are commonly used in everyday devices like thermostats to enhance system damping and reduce steady-state error. When the zero in the controller's transfer function is optimally placed, the system benefits significantly in terms of stability and accuracy.
Acting as a low-pass filter, the PI controller slows the system's response and extends settling times. This requires...
234
Stability of Equilibrium Configuration: Problem Solving01:13

Stability of Equilibrium Configuration: Problem Solving

731
The stability of equilibrium configurations is an important concept in physics, engineering, and other related fields. In simple terms, it refers to the tendency of an object or system to return to its equilibrium position after being disturbed. The stability of an equilibrium configuration can be analyzed by considering the potential energy function of the system and examining its behavior near the equilibrium point.
Problem-solving in the context of the stability of equilibrium configuration...
731
PI Controller: Design01:24

PI Controller: Design

656
Proportional Integral (PI) controllers are a fundamental component in modern control systems, widely used to enhance performance and mitigate steady-state errors. They are particularly effective in applications such as automatic brightness adjustment on smartphones, where they excel at mitigating steady-state errors for step-function inputs. Unlike PD controllers, which require time-varying errors to function optimally, PI controllers leverage their integral component to address residual...
656

You might also read

Related Articles

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

Sort by
Same author

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: Oct 26, 2025

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
11:54

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

Published on: May 8, 2021

4.8K

Stabilizing Large-Scale Probabilistic Boolean Networks by Pinning Control.

Lin Lin, Jinde Cao, Jianquan Lu

    IEEE Transactions on Cybernetics
    |August 3, 2021
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a new pinning control strategy to stabilize probabilistic Boolean networks (PBNs). The method enhances control by using both mode-independent and mode-dependent controllers for gene regulatory networks.

    More Related Videos

    A New Toolkit for Evaluating Gene Functions using Conditional Cas9 Stabilization
    08:20

    A New Toolkit for Evaluating Gene Functions using Conditional Cas9 Stabilization

    Published on: September 2, 2021

    4.3K
    Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
    10:44

    Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

    Published on: December 7, 2021

    2.4K

    Related Experiment Videos

    Last Updated: Oct 26, 2025

    Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
    11:54

    Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

    Published on: May 8, 2021

    4.8K
    A New Toolkit for Evaluating Gene Functions using Conditional Cas9 Stabilization
    08:20

    A New Toolkit for Evaluating Gene Functions using Conditional Cas9 Stabilization

    Published on: September 2, 2021

    4.3K
    Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
    10:44

    Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

    Published on: December 7, 2021

    2.4K

    Area of Science:

    • Systems Biology
    • Control Theory
    • Computational Biology

    Background:

    • Probabilistic Boolean networks (PBNs) model gene regulatory networks with inherent stochasticity.
    • The probabilistic nature of PBNs poses challenges for traditional control strategies.
    • Existing control methods may struggle with the complexity and scale of biological networks.

    Purpose of the Study:

    • To develop a novel pinning control strategy for stabilizing probabilistic Boolean networks (PBNs).
    • To address the limitations of mode-independent controllers in stochastic PBNs.
    • To provide a more practicable approach for large-scale and sparsely connected networks.

    Main Methods:

    • A novel pinning control strategy is proposed, incorporating both mode-independent and mode-dependent controllers.
    • A criterion is derived to assess the applicability of mode-independent controllers.
    • The control strategy is based on the n×n network structure, not the 2^n × 2^n state transition matrix.

    Main Results:

    • The proposed pinning control strategy effectively stabilizes PBNs.
    • The method is shown to be more practicable and scalable than existing approaches.
    • A criterion for mode-independent controller applicability is successfully derived.

    Conclusions:

    • The novel pinning control strategy offers an effective and scalable solution for stabilizing probabilistic Boolean networks.
    • This approach is particularly beneficial for large-scale and sparsely connected biological networks.
    • The developed control scheme provides a robust method for analyzing gene regulatory dynamics, including in disease models.