Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Feedback control systems

Feedback control systems

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...

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

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,...

Transfer Function in Control Systems

Transfer Function in Control Systems

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...

Combinatorial Gene Control

Combinatorial Gene Control

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...

Control System Problem

Control System Problem

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...

Control Systems

Control Systems

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...

You might also read

Related Articles

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

Sort by

Same authorSame journal

A Collaborative Neurodynamic Approach to Sharpness-Aware Minimization for Improving Generalization of Deep Learning.

IEEE transactions on cybernetics·2026

Same author

A Three-Dimensional Covalent Organic Framework Enables Guest-Triggered Reversible Disorder-Order Structural Adaptation for SO<b><sub>2</sub></b> Adsorption.

Journal of the American Chemical Society·2026

Same author

Chemotherapy-induced peripheral neuropathy and social interaction anxiety in breast cancer patients: a cross-sectional study.

BMC women's health·2026

Same author

Annexin A2 Is Associated with Dietary Cholesterol-Induced Metabolic Dysregulation and the Progression of Hepatic Fibrosis.

Metabolites·2026

Same author

Summary of the evidence on TCM nonpharmacological interventions for cognitive impairment in patients with Alzheimer's disease.

Geriatric nursing (New York, N.Y.)·2026

Same author

HoStB-DVGNN: A Flotation Fault Recognition Method Using Higher Order Spatial-Temporal Block and Dual-Stream Variational GNN.

IEEE transactions on cybernetics·2026

Search research articles

Related Experiment Video

Updated: Jan 20, 2026

Control of Eating Behavior Using a Novel Feedback System

Control of Eating Behavior Using a Novel Feedback System

Published on: May 8, 2018

Sampled-Data State-Feedback Stabilization of Probabilistic Boolean Control Networks: A Control Lyapunov Function

Jiayang Liu, Yang Liu, Yuqian Guo

IEEE Transactions on Cybernetics

|August 24, 2019

Summary

This study addresses partial stabilization for probabilistic Boolean control networks (PBCNs) using sample-data state-feedback control (SDSFC). It establishes conditions for control Lyapunov function (CLF) existence, enabling controller design for robust system stabilization.

More Related Videos

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

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

Published on: June 19, 2016

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

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

Published on: February 23, 2024

Related Experiment Videos

Last Updated: Jan 20, 2026

Control of Eating Behavior Using a Novel Feedback System

Control of Eating Behavior Using a Novel Feedback System

Published on: May 8, 2018

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

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

Published on: June 19, 2016

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

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

Published on: February 23, 2024

Area of Science:

Control Theory
Networked Systems
Boolean Networks

Background:

Probabilistic Boolean Control Networks (PBCNs) present complex dynamics.
Partial stabilization is crucial for controlling specific network behaviors.
Sample-data state-feedback control (SDSFC) is a practical control strategy.

Purpose of the Study:

To investigate the partial stabilization problem of PBCNs under SDSFC.
To develop a Control Lyapunov Function (CLF) approach for PBCNs.
To design effective SDSFC controllers for PBCNs.

Main Methods:

Representing PBCN probability structure matrix using a Boolean matrix.
Converting partial stabilization to global set stabilization.
Defining CLF and its structural matrix under SDSFC.
Deriving necessary and sufficient conditions for CLF existence.

Main Results:

A new algebraic form for PBCNs was obtained.
The existence of a CLF is equivalent to the existence of an SDSFC.
A necessary and sufficient condition for CLF existence under SDSFC was derived.
Two distinct methods were presented for designing SDSFC controllers and CLF structural matrices.

Conclusions:

The study provides a robust framework for partial stabilization of PBCNs using SDSFC.
The developed CLF approach offers a systematic way to design stabilizing controllers.
The findings are validated through illustrative examples, demonstrating practical applicability.