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

Propagation of Uncertainty from Random Error00:59

Propagation of Uncertainty from Random Error

1.8K
An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...
1.8K
Propagation of Uncertainty from Systematic Error01:10

Propagation of Uncertainty from Systematic Error

1.4K
The atomic mass of an element varies due to the relative ratio of its isotopes. A sample's relative proportion of oxygen isotopes influences its average atomic mass. For instance, if we were to measure the atomic mass of oxygen from a sample, the mass would be a weighted average of the isotopic masses of oxygen in that sample. Since a single sample is not likely to perfectly reflect the true atomic mass of oxygen for all the molecules of oxygen on Earth, the mass we obtain from this...
1.4K
Time-Domain Interpretation of PD Control01:07

Time-Domain Interpretation of PD Control

377
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...
377
Multimachine Stability01:25

Multimachine Stability

548
Multimachine stability analysis is crucial for understanding the dynamics and stability of power systems with multiple synchronous machines. The objective is to solve the swing equations for a network of M machines connected to an N-bus power system.
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:
548
Time and frequency -Domain Interpretation of Phase-lag Control01:21

Time and frequency -Domain Interpretation of Phase-lag Control

396
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...
396
Collisions in Multiple Dimensions: Problem Solving01:06

Collisions in Multiple Dimensions: Problem Solving

5.3K
In multiple dimensions, the conservation of momentum applies in each direction independently. Hence, to solve collisions in multiple dimensions, we should write down the momentum conservation in each direction separately. To help understand collisions in multiple dimensions, consider an example.
A small car of mass 1,200 kg traveling east at 60 km/h collides at an intersection with a truck of mass 3,000 kg traveling due north at 40 km/h. The two vehicles are locked together. What is the...
5.3K

You might also read

Related Articles

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

Sort by
Same author

Forecasting seasonal allergic rhinitis through integrated analysis of social media and online drug sales data.

The World Allergy Organization journal·2026
Same author

Integrated Microbiomics and Metabolomics Reveal That Moisture Content and <i>Lactiplantibacillus plantarum</i> Synergistically Regulate Fermentation Quality, Microbial Community, and Metabolite Profiles of Amaranth Silage.

Microorganisms·2026
Same author

Online Value Iteration for Unknown Nonlinear Multiagent Systems: A Model-Decoupled Encoding-Decoding Mechanism.

IEEE transactions on neural networks and learning systems·2026
Same author

Astragalus Polysaccharides Attenuate LPS-Induced Degenerative Responses in Primary Rat Chondrocytes linked to the NLRP3/CASPASE-1 Axis.

Journal of musculoskeletal & neuronal interactions·2026
Same author

Contaminative Data-Driven Koopman Resilient Distributed Filtering for Unknown Stochastic Nonlinear Systems.

IEEE transactions on neural networks and learning systems·2026
Same author

Dissipativity-Based Output Feedback Control of Networked Sampled-Data Systems Under Actuator Failures and Consecutive DoS Attacks.

IEEE transactions on cybernetics·2026

Related Experiment Video

Updated: Jan 18, 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

5.1K

Limited Impulsive Control of Time-Delay Multiagent Systems With Packet Loss and Parameter Mismatch.

Le You, Xiaowei Jiang, Chuan-Ke Zhang

    IEEE Transactions on Cybernetics
    |September 8, 2025
    PubMed
    Summary

    This study achieves leader-following consensus in nonlinear multiagent systems with time delays using novel impulsive control. It addresses packet loss and parameter mismatch for robust real-world applications.

    More Related Videos

    Measuring Delay Discounting in Humans Using an Adjusting Amount Task
    07:47

    Measuring Delay Discounting in Humans Using an Adjusting Amount Task

    Published on: January 9, 2016

    16.0K

    Related Experiment Videos

    Last Updated: Jan 18, 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

    5.1K
    Measuring Delay Discounting in Humans Using an Adjusting Amount Task
    07:47

    Measuring Delay Discounting in Humans Using an Adjusting Amount Task

    Published on: January 9, 2016

    16.0K

    Area of Science:

    • Control Theory
    • Systems Engineering
    • Networked Systems

    Background:

    • Achieving consensus in multiagent systems is crucial for coordinated behavior.
    • Nonlinear systems with time delays present significant control challenges.
    • Real-world communication constraints like packet loss and parameter mismatch impede consensus.

    Purpose of the Study:

    • To investigate leader-following consensus in nonlinear time-delay multiagent systems.
    • To develop novel impulsive control protocols addressing packet loss and parameter mismatch.
    • To establish robust consensus criteria under practical communication imperfections.

    Main Methods:

    • Development of two impulsive control protocols: pure impulsive and limited impulsive schemes.
    • Introduction of an auxiliary function to model packet loss phenomena.
    • Integration of impulsive control theory with reverse average dwell-time analysis.

    Main Results:

    • Sufficient consensus criteria derived for multiagent systems with time delays and heterogeneous parameters.
    • Proposed control framework demonstrates effectiveness in achieving consensus.
    • Validation through numerical simulations under practical communication imperfections.

    Conclusions:

    • The proposed impulsive control framework effectively achieves leader-following consensus.
    • The study successfully addresses challenges of packet loss and parameter mismatch.
    • The findings are applicable to real-world networked systems with communication constraints.