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

Master Transcription Regulators

Master Transcription Regulators

Master transcription regulators are regulatory proteins that are predominantly responsible for regulating the expression of multiple genes. Often these genes work in concert to drive a complex process. Activation of a master transcription regulator can lead to a cascade of transcriptional activation necessary for that outcome. These regulators can directly bind to the regulatory sequences of the various genes involved, or they can indirectly regulate transcription by binding to regulatory...

Master Transcription Regulators

Master Transcription Regulators

Simplified Synchronous Machine Model

Simplified Synchronous Machine Model

The Synchronous Machine Model is a fundamental tool in analyzing and ensuring the transient stability of power systems. This model simplifies the representation of a synchronous machine under balanced three-phase positive-sequence conditions, assuming constant excitation and ignoring losses and saturation. The model is pivotal for understanding the behavior of synchronous generators connected to a power grid, particularly during transient events.
In this model, each generator is connected to a...

Approximate Integration

Approximate Integration

In many practical and theoretical contexts, the exact value of a definite integral may be inaccessible. This limitation typically arises when the antiderivative of a function is either unknown or cannot be expressed in a closed mathematical form. Alternatively, it can occur when a function is defined not by a formula but by a finite set of empirical data points, such as those collected during experiments. In these cases, approximate integration techniques provide a valuable solution.One of the...

Linearization and Approximation

Linearization and Approximation

Linearization is a mathematical technique used to approximate complex, nonlinear functions with simpler linear models in the vicinity of a chosen reference point. The method is based on the idea that, although a function may be difficult to evaluate exactly, its behavior near a specific input value can often be closely approximated by the tangent line at that point. This approach is particularly useful when small deviations from a known value are involved.Consider the square root function, for...

Application of Linearization and Approximation

Application of Linearization and Approximation

A drone flying through complex terrain often relies on more than one sensing method to estimate small changes in altitude. Along with direct measurements, air pressure provides a useful indirect indicator of vertical movement. Atmospheric pressure decreases as altitude increases, and this relationship is commonly described using an exponential model. Although accurate, converting pressure measurements into altitude values requires calculations that are too complex to perform repeatedly during...

You might also read

Related Articles

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

Sort by

Same author

Prostate Cancer Biomarkers with a Focus on Galectin-3: Emerging Clinical and Therapeutic Implications.

Current oncology (Toronto, Ont.)·2026

Same author

Vibration-based bearing fault diagnosis in noisy conditions using matrix pencil mean frequency and multilayer perceptron neural networks.

PloS one·2026

Same author

Development of injectable ibuprofen and resveratrol co-loaded mesoporous silica nanoparticle-based hydrogels for sustained delivery in osteoarthritis management.

Journal of pharmaceutical sciences·2026

Same author

Folic Acid-Chitosan Conjugated Mesoporous Silica Nanoparticles for Enhanced Piceatannol Uptake in MCF‑7 Breast Cancer Cells.

ACS omega·2025

Same author

Machine learning identification of molecular targets for medulloblastoma subgroups using microarray gene fingerprint analysis.

Computational and structural biotechnology journal·2025

Same author

A "proto" type galectin expressed in striped bass (<i>Morone saxatilis</i>) tissues is released to epidermal mucus and binds to bacterial and mucus glycans.

Frontiers in cellular and infection microbiology·2025

Search research articles

Related Experiment Video

Updated: Feb 15, 2026

How to Calculate and Validate Inter-brain Synchronization in a fNIRS Hyperscanning Study

How to Calculate and Validate Inter-brain Synchronization in a fNIRS Hyperscanning Study

Published on: September 8, 2021

Robust synchronization of master-slave chaotic systems using approximate model: An experimental study.

Hafiz Ahmed¹, Ivan Salgado², Héctor Ríos³

¹School of Mechanical, Aerospace and Automotive Engineering, Coventry University, Coventry, CV1 5FB, UK.

ISA Transactions

|January 15, 2018

Summary

This summary is machine-generated.

This study achieves robust synchronization of chaotic systems using a novel Continuous Singular Terminal Sliding-Mode (CSTSM) controller. The method employs ultra-local models and higher-order sliding-mode differentiators for effective state estimation and control.

Keywords:

Chaotic systems Master-slave synchronization Model-free control Robust synchronization Sliding-mode

More Related Videos

Psychophysically-anchored, Robust Thresholding in Studying Pain-related Lateralization of Oscillatory Prestimulus Activity

Psychophysically-anchored, Robust Thresholding in Studying Pain-related Lateralization of Oscillatory Prestimulus Activity

Published on: January 21, 2017

Study of Experimental Organ Donation Models for Lung Transplantation

Study of Experimental Organ Donation Models for Lung Transplantation

Published on: March 15, 2024

Related Experiment Videos

Last Updated: Feb 15, 2026

How to Calculate and Validate Inter-brain Synchronization in a fNIRS Hyperscanning Study

How to Calculate and Validate Inter-brain Synchronization in a fNIRS Hyperscanning Study

Published on: September 8, 2021

Psychophysically-anchored, Robust Thresholding in Studying Pain-related Lateralization of Oscillatory Prestimulus Activity

Psychophysically-anchored, Robust Thresholding in Studying Pain-related Lateralization of Oscillatory Prestimulus Activity

Published on: January 21, 2017

Study of Experimental Organ Donation Models for Lung Transplantation

Study of Experimental Organ Donation Models for Lung Transplantation

Published on: March 15, 2024

Area of Science:

Control Systems Engineering
Nonlinear Dynamics
Chaos Theory

Background:

Master-slave chaotic systems exhibit complex, unpredictable behavior.
Achieving robust synchronization is crucial for secure communication and signal processing applications.
Existing synchronization methods often require full state information or are sensitive to noise.

Purpose of the Study:

To develop a robust output feedback control strategy for synchronizing master-slave chaotic systems.
To utilize the ultra-local model concept for approximating system dynamics.
To design a Continuous Singular Terminal Sliding-Mode (CSTSM) controller for enhanced synchronization performance.

Main Methods:

Obtaining an approximate model of the error system using the ultra-local model concept.
Designing a Continuous Singular Terminal Sliding-Mode (CSTSM) controller.
Employing a fixed-time higher-order sliding-mode (HOSM) differentiator for state estimation from system outputs.
Implementing an output feedback control scheme.

Main Results:

The proposed CSTSM controller effectively achieves robust synchronization between master and slave chaotic systems.
The use of ultra-local models simplifies system representation for control design.
The HOSM differentiator provides accurate state estimation, even with output measurements.
Numerical simulations and experimental results validate the controller's effectiveness.

Conclusions:

The presented output feedback control strategy ensures robust synchronization of chaotic systems.
The combination of ultra-local modeling and CSTSM control offers a powerful approach for chaos synchronization.
The fixed-time HOSM differentiator is a key component for practical implementation using only system outputs.