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

Time-Domain Interpretation of PD Control01:07

Time-Domain Interpretation of PD Control

322
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...
322
Linear time-invariant Systems01:23

Linear time-invariant Systems

802
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...
802
BIBO stability of continuous and discrete -time systems01:24

BIBO stability of continuous and discrete -time systems

841
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....
841
Transfer Function in Control Systems01:21

Transfer Function in Control Systems

1.4K
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...
1.4K
Time and frequency -Domain Interpretation of Phase-lag Control01:21

Time and frequency -Domain Interpretation of Phase-lag Control

348
Phase-lag controllers are widely used in control systems to improve stability and reduce steady-state errors. A dimmer switch controlling the brightness of a light bulb serves as a practical example of phase-lag control, gradually adjusting the bulb's brightness. Mathematically, phase-lag control or low-pass filtering is represented when the factor 'a' is less than 1.
Phase-lag controllers do not place a pole at zero, but instead influence the steady-state error by amplifying any...
348
Phase-lead and Phase-lag Controllers01:22

Phase-lead and Phase-lag Controllers

476
Understanding the working function of different types of controllers can be illustrated with practical analogies, such as adjusting a stereo's volume equalizer. Cranking up the bass involves a phase-lead controller, which functions as a high-pass filter, while increasing the treble uses a phase-lag controller, which acts as a low-pass filter. PD controllers, similar to high-pass filters, enhance the system's response to high-frequency components. PI controllers, akin to low-pass...
476

You might also read

Related Articles

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

Sort by
Same author

The coherence analysis and Laplacian spectrum applications of cycle-based iterative networks.

Chaos (Woodbury, N.Y.)·2026
Same author

Optimized predefined-time control for high-order nonlinear MASs via ICA and reinforcement learning.

ISA transactions·2026
Same author

Data-Driven Optimized Output Regulation for Markov Jump Linear Systems and Its Application.

IEEE transactions on cybernetics·2026
Same author

Innovations in Electrochemical Sensors for TNT Explosive Detection: From Nanomaterials to Wearable Devices and Artificial Intelligence.

Critical reviews in analytical chemistry·2026
Same author

Turing instability and pattern formation in a diffusive predator-prey system with opportunistic predators and weak Allee effect.

Physical review. E·2026
Same author

Stochastic-Sampling-Based Event-Triggered Control for Switching Reaction-Diffusion Neural Networks.

IEEE transactions on cybernetics·2026

Related Experiment Video

Updated: Dec 26, 2025

Using Neuron Spiking Activity to Trigger Closed-Loop Stimuli in Neurophysiological Experiments
05:19

Using Neuron Spiking Activity to Trigger Closed-Loop Stimuli in Neurophysiological Experiments

Published on: November 12, 2019

7.4K

Synchronization Analysis for Complex Dynamical Networks With Coupling Delay via Event-Triggered Delayed Impulsive

Xiaoxiao Lv, Jinde Cao, Xiaodi Li

    IEEE Transactions on Cybernetics
    |March 10, 2020
    PubMed
    Summary

    This study introduces an event-triggered delayed impulsive control (ETDIC) strategy for complex dynamical networks (CDNs) with coupling delay. The novel approach ensures exponential synchronization while addressing network issues like packet loss.

    More Related Videos

    Age-dependent Dynamics of Locomotion in Caenorhabditis elegans: A Lyapunov Exponent Analysis
    06:44

    Age-dependent Dynamics of Locomotion in Caenorhabditis elegans: A Lyapunov Exponent Analysis

    Published on: September 23, 2025

    426
    Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator
    06:04

    Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator

    Published on: February 14, 2025

    928

    Related Experiment Videos

    Last Updated: Dec 26, 2025

    Using Neuron Spiking Activity to Trigger Closed-Loop Stimuli in Neurophysiological Experiments
    05:19

    Using Neuron Spiking Activity to Trigger Closed-Loop Stimuli in Neurophysiological Experiments

    Published on: November 12, 2019

    7.4K
    Age-dependent Dynamics of Locomotion in Caenorhabditis elegans: A Lyapunov Exponent Analysis
    06:44

    Age-dependent Dynamics of Locomotion in Caenorhabditis elegans: A Lyapunov Exponent Analysis

    Published on: September 23, 2025

    426
    Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator
    06:04

    Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator

    Published on: February 14, 2025

    928

    Area of Science:

    • Control Theory
    • Network Science
    • Dynamical Systems

    Background:

    • Complex dynamical networks (CDNs) often face synchronization challenges due to coupling delays.
    • Existing control strategies may be inefficient or susceptible to network imperfections like packet loss.

    Purpose of the Study:

    • To develop a novel event-triggered delayed impulsive control (ETDIC) strategy for achieving exponential synchronization in CDNs with coupling delay.
    • To address network issues such as packet loss, misordering, and retransmission within the control framework.

    Main Methods:

    • Formulation of the ETDIC strategy based on a quadratic Lyapunov function.
    • Utilizing the Lyapunov-Razumikhin (L-R) technique and impulsive control theory.
    • Derivation of sufficient conditions for synchronization using linear matrix inequalities (LMIs).

    Main Results:

    • The proposed ETDIC strategy effectively guarantees exponential synchronization in CDNs.
    • The strategy successfully eliminates the Zeno phenomenon.
    • Conditions for synchronization are less conservative, as demonstrated by LMIs.

    Conclusions:

    • The ETDIC strategy provides a robust and efficient method for exponential synchronization in complex dynamical networks.
    • The approach is validated through numerical simulations, confirming its practical effectiveness.