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

BIBO stability of continuous and discrete -time systems01:24

BIBO stability of continuous and discrete -time systems

1.0K
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....
1.0K
Linear time-invariant Systems01:23

Linear time-invariant Systems

1.0K
A system is linear if it displays the characteristics of homogeneity and additivity, together termed the superposition property. This principle is fundamental in all linear systems. Linear time-invariant (LTI) systems include systems with linear elements and constant parameters.
The input-output behavior of an LTI system can be fully defined by its response to an impulsive excitation at its input. Once this impulse response is known, the system's reaction to any other input can be...
1.0K
State Space Representation01:27

State Space Representation

643
The frequency-domain technique, commonly used in analyzing and designing feedback control systems, is effective for linear, time-invariant systems. However, it falls short when dealing with nonlinear, time-varying, and multiple-input multiple-output systems. The time-domain or state-space approach addresses these limitations by utilizing state variables to construct simultaneous, first-order differential equations, known as state equations, for an nth-order system.
Consider an RLC circuit, a...
643
Time-Domain Interpretation of PD Control01:07

Time-Domain Interpretation of PD Control

426
Proportional-Derivative (PD) control is a widely used control method in various engineering systems to enhance stability and performance. In a system with only proportional control, common issues include high maximum overshoot and oscillation, observed in both the error signal and its rate of change. This behavior can be divided into three distinct phases: initial overshoot, subsequent undershoot, and gradual stabilization.
Consider the example of control of motor torque. Initially, a positive...
426
Drug Concentration Versus Time Correlation01:15

Drug Concentration Versus Time Correlation

2.5K
The plasma drug concentration-time curve is a crucial tool in pharmacokinetics, representing the drug's concentration in plasma at different time intervals post-administration. This curve illustrates the drug's journey from absorption into the systemic circulation, distribution to body tissues, and eventual elimination through excretion or biotransformation.
Two pivotal parameters are the minimum effective concentration (MEC) and the minimum toxic concentration (MTC). The MEC is the...
2.5K
Cyclic Processes And Isolated Systems01:19

Cyclic Processes And Isolated Systems

3.6K
A thermodynamic system with zero heat exchange and work is an isolated system. For these systems, the internal energy remains constant.
In the case of a non-isolated system, the change in the internal energy is zero only if the process is cyclic. A thermodynamic process is considered cyclic if the system undergoes a series of changes and returns to its initial state. 
Consider a cyclic process that returns to its initial state, undergoing a four-step process. The heat transfer along each...
3.6K

You might also read

Related Articles

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

Sort by
Same author

Improving tenderness and quality of camel meat through ultrasound and papain treatment: Insights from structural and proteomics analysis.

Food chemistry: X·2026
Same author

Stability analysis of impulsive systems with impulse-dependent varying delay: A MDI-based looped functional approach.

Neural networks : the official journal of the International Neural Network Society·2026
Same author

Cell-type specific allelic dampening of sex-linked genes in sex chromosome aneuploidy.

bioRxiv : the preprint server for biology·2026
Same author

Event-triggered control of nonlinear networked control systems via a data-based representation.

ISA transactions·2026
Same author

A comparison of spheno-occipital synchondrosis fusion, hand-wrist maturation, and cervical vertebral maturation for assessing skeletal maturation in Chinese adolescents: A cross-sectional study.

International orthodontics·2026
Same author

Two-Stage Asynchronous Learning for Optimal Tracking in Multiplayer Differential Games.

IEEE transactions on cybernetics·2026

Related Experiment Video

Updated: Mar 8, 2026

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

5.2K

Nonfragile Exponential Synchronization of Delayed Complex Dynamical Networks With Memory Sampled-Data Control.

Yajuan Liu, Bao-Zhu Guo, Ju H Park

    IEEE Transactions on Neural Networks and Learning Systems
    |January 24, 2017
    PubMed
    Summary

    This study introduces novel nonfragile sampled-data control for complex dynamical networks (CDNs) with time-varying delays, ensuring exponential synchronization despite uncertainties. The methods guarantee system stability and are easily implemented using linear matrix inequalities.

    More Related Videos

    Real-time Electrophysiology: Using Closed-loop Protocols to Probe Neuronal Dynamics and Beyond
    08:08

    Real-time Electrophysiology: Using Closed-loop Protocols to Probe Neuronal Dynamics and Beyond

    Published on: June 24, 2015

    12.1K
    Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons
    07:59

    Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons

    Published on: June 9, 2023

    2.0K

    Related Experiment Videos

    Last Updated: Mar 8, 2026

    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

    5.2K
    Real-time Electrophysiology: Using Closed-loop Protocols to Probe Neuronal Dynamics and Beyond
    08:08

    Real-time Electrophysiology: Using Closed-loop Protocols to Probe Neuronal Dynamics and Beyond

    Published on: June 24, 2015

    12.1K
    Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons
    07:59

    Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons

    Published on: June 9, 2023

    2.0K

    Area of Science:

    • Control Theory
    • Networked Systems
    • Dynamical Systems

    Background:

    • Complex dynamical networks (CDNs) often exhibit synchronization phenomena crucial for various applications.
    • Time-varying coupling delays and norm-bounded uncertainties pose significant challenges to achieving robust synchronization.
    • Existing control strategies may not adequately address the combined effects of these factors.

    Purpose of the Study:

    • To develop a nonfragile sampled-data feedback control strategy for achieving exponential synchronization in CDNs.
    • To address the complexities introduced by time-varying coupling delays and norm-bounded uncertainties.
    • To present easily implementable conditions for guaranteed synchronization.

    Main Methods:

    • Construction of a novel augmented Lyapunov function.
    • Utilization of integral inequalities and the convex combination technique.
    • Formulation of control conditions within the linear matrix inequality (LMI) framework.

    Main Results:

    • A sufficient condition for nonfragile exponential stability of the error system is derived.
    • New sampled-data synchronization criteria are presented for CDNs with time-varying coupling delay.
    • The proposed conditions are demonstrated to be easily solvable and implementable.

    Conclusions:

    • The developed sampled-data control effectively achieves nonfragile exponential synchronization in CDNs.
    • The LMI-based approach offers a practical and efficient method for designing controllers.
    • The findings are validated through illustrative examples, showcasing the control's effectiveness.