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

Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

686
Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...
686
Stability of Equilibrium Configuration: Problem Solving01:13

Stability of Equilibrium Configuration: Problem Solving

637
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...
637
BIBO stability of continuous and discrete -time systems01:24

BIBO stability of continuous and discrete -time systems

463
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....
463
Alternative Sets of Equilibrium Equations01:31

Alternative Sets of Equilibrium Equations

431
When analyzing the behavior of structures, engineers often rely on the concept of equilibrium. This refers to the state where all forces and moments acting on a system balance each other, resulting in no net movement or rotation. In many cases, equilibrium can be described by a set of standard equations. However, in some situations, alternative sets of equilibrium equations must be used to describe the system's behavior accurately.
One example of such a situation can be observed in a...
431
Linear time-invariant Systems01:23

Linear time-invariant Systems

311
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...
311
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

134
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
134

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

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
Same author

Passivity and synchronization of fractional-order coupled neural networks with multiple weights: A PD approach.

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

Related Experiment Video

Updated: Aug 4, 2025

The HoneyComb Paradigm for Research on Collective Human Behavior
06:48

The HoneyComb Paradigm for Research on Collective Human Behavior

Published on: January 19, 2019

9.4K

Aperiodically Intermittent Event-Triggered Optimal Average Consensus for Nonlinear Multi-Agent Systems.

Lei Liu, Jinde Cao, Fawaz E Alsaadi

    IEEE Transactions on Neural Networks and Learning Systems
    |April 6, 2023
    PubMed
    Summary

    This study introduces a new intermittent event-triggered strategy for achieving average consensus in multi-agent systems. The research also develops an optimal strategy using adaptive dynamic programming and neural networks.

    More Related Videos

    WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control
    08:18

    WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control

    Published on: August 15, 2020

    5.0K
    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

    4.5K

    Related Experiment Videos

    Last Updated: Aug 4, 2025

    The HoneyComb Paradigm for Research on Collective Human Behavior
    06:48

    The HoneyComb Paradigm for Research on Collective Human Behavior

    Published on: January 19, 2019

    9.4K
    WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control
    08:18

    WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control

    Published on: August 15, 2020

    5.0K
    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

    4.5K

    Area of Science:

    • Control Engineering
    • Distributed Systems
    • Optimization Theory

    Background:

    • Achieving average consensus in multi-agent systems is crucial for coordinated behavior.
    • Existing event-triggered strategies can be inefficient or complex.
    • Optimizing consensus strategies is essential for practical applications.

    Purpose of the Study:

    • To design a novel intermittent event-triggered strategy for average consensus.
    • To investigate the optimality of the consensus strategy.
    • To develop an adaptive dynamic programming algorithm for the optimal strategy.

    Main Methods:

    • Designing a novel intermittent event-triggered condition.
    • Establishing a piecewise differential inequality.
    • Deriving Nash equilibrium and Hamilton-Jacobi-Bellman equations.
    • Implementing an actor-critic neural network architecture.

    Main Results:

    • Several criteria for achieving average consensus were obtained.
    • The optimal intermittent event-triggered strategy was derived.
    • An adaptive dynamic programming algorithm and its neural network implementation were presented.
    • Numerical examples demonstrated the strategy's feasibility and effectiveness.

    Conclusions:

    • The proposed intermittent event-triggered strategy effectively achieves average consensus in multi-agent systems.
    • The developed optimal strategy and adaptive dynamic programming approach offer efficient solutions.
    • The findings contribute to the advancement of distributed control and optimization techniques.