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

Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

142
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...
142
Collisions in Multiple Dimensions: Problem Solving01:06

Collisions in Multiple Dimensions: Problem Solving

4.3K
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...
4.3K
Fixed Action Patterns01:06

Fixed Action Patterns

16.4K
A fixed action pattern (FAP) is a specific, hard-wired sequence of behaviors that occurs in response to an external stimulus, called a sign stimulus. The behavior is “fixed” because it is essentially unchangeable—proceeding similarly across individuals of a species every time it occurs.
16.4K
Masking and Demasking Agents01:19

Masking and Demasking Agents

2.6K
EDTA titrations may necessitate masking and demasking agents to temporarily protect a particular metal ion in a mixture from the EDTA reaction. These agents facilitate the sequential analysis of the metal ions by forming stable complexes with some—but not all—metal ions during certain steps.
There are many masking agents, such as cyanide, fluoride, triethanolamine, thiourea, and 2,3-bis(sulfanyl)propan-1-ol (formerly 2,3-dimercapto-1-propanol), with the masking agent chosen based on...
2.6K
Collisions in Multiple Dimensions: Introduction01:05

Collisions in Multiple Dimensions: Introduction

5.5K
It is far more common for collisions to occur in two dimensions; that is, the initial velocity vectors are neither parallel nor antiparallel to each other. Let's see what complications arise from this. The first idea is that momentum is a vector. Like all vectors, it can be expressed as a sum of perpendicular components (usually, though not always, an x-component and a y-component, and a z-component if necessary). Thus, when the statement of conservation of momentum is written for a...
5.5K
Associative Learning01:27

Associative Learning

525
Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
Classical conditioning, also known...
525

You might also read

Related Articles

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

Sort by
Same author

Image-Based Deep Learning for Cataract Diagnosis: Systematic Review and Meta-Analysis.

Journal of medical Internet research·2026
Same author

A latent profile analysis of hierarchical management of supportive care needs in patients undergoing maintenance hemodialysis.

Scientific reports·2026
Same author

Construction of donkey skin fibroblast immortalized cell line and comparative analysis with primary cells.

Tissue & cell·2026
Same author

Phase-velocity-reversed topological edge states and rainbows for field enhancement and radiation control.

Optics letters·2026
Same author

Multiple Dose Reduction Techniques With Subtraction Coronary CT Angiography for Patients With High Calcification Scores.

Journal of computer assisted tomography·2026
Same author

Clinical evaluation of probe capture based targeted next generation sequencing for pulmonary infection in immunocompromised patients: a cross-sectional diagnostic accuracy study.

Infectious diseases (London, England)·2026
Same journal

Granular Ball-Based Noise-Resistant Fuzzy Multineighborhood Feature Selection via Label Enhancement and Feature Graph.

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

Fighting Evolving Spam With ARTMAP Models: A Noise-Resilient Online Detection Framework.

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

HyperSAT: Unsupervised Hypergraph Neural Networks for Weighted MaxSAT Problems.

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

Negation of Basic Belief Assignment in Multisource Information Fusion on Dempster-Shafer Theory With Applications in Pattern Classification.

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

Intervention Feasible Region and Driver Risk Capacity Aware Human-Machine Collaborative Safe Trajectory Planning.

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

A Unified Differential Denoising Learning Framework With a Pre-Trained Model and Fuzzy Graph Networks for Drug-Drug Interaction Prediction.

IEEE transactions on neural networks and learning systems·2026
See all related articles

Related Experiment Video

Updated: Aug 26, 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

9.5K

Event-Based Adaptive NN Fixed-Time Cooperative Formation for Multiagent Systems.

Liang Cao, Zhijian Cheng, Yang Liu

    IEEE Transactions on Neural Networks and Learning Systems
    |October 10, 2022
    PubMed
    Summary
    This summary is machine-generated.

    This study presents a neural network-based control strategy for nonlinear multiagent systems (MASs) to achieve fixed-time formation control despite dynamic uncertainties and limited communication. The method ensures stability and reduces communication load for improved MAS performance.

    More Related Videos

    Inter-Brain Synchrony in Open-Ended Collaborative Learning: An fNIRS-Hyperscanning Study
    04:44

    Inter-Brain Synchrony in Open-Ended Collaborative Learning: An fNIRS-Hyperscanning Study

    Published on: July 21, 2021

    4.3K
    An Optogenetic Approach for Assessing Formation of Neuronal Connections in a Co-culture System
    11:22

    An Optogenetic Approach for Assessing Formation of Neuronal Connections in a Co-culture System

    Published on: February 17, 2015

    13.6K

    Related Experiment Videos

    Last Updated: Aug 26, 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

    9.5K
    Inter-Brain Synchrony in Open-Ended Collaborative Learning: An fNIRS-Hyperscanning Study
    04:44

    Inter-Brain Synchrony in Open-Ended Collaborative Learning: An fNIRS-Hyperscanning Study

    Published on: July 21, 2021

    4.3K
    An Optogenetic Approach for Assessing Formation of Neuronal Connections in a Co-culture System
    11:22

    An Optogenetic Approach for Assessing Formation of Neuronal Connections in a Co-culture System

    Published on: February 17, 2015

    13.6K

    Area of Science:

    • Control Systems Engineering
    • Robotics
    • Artificial Intelligence

    Background:

    • Multiagent systems (MASs) face challenges in formation control due to dynamic uncertainties and communication constraints.
    • Existing methods often struggle with prescribed performance and zero equilibrium point issues.

    Purpose of the Study:

    • To develop a fixed-time formation control strategy for nonlinear MASs.
    • To address dynamic uncertainties and limited communication resources effectively.
    • To achieve prescribed transient and steady-state performance.

    Main Methods:

    • A neural network (NN)-based composite dynamic surface control (CDSC) strategy is proposed.
    • A fixed-time prescribed performance function (FTPPF) is designed to ensure performance bounds.
    • Disturbance observers and an improved dynamic event-triggered mechanism are utilized.

    Main Results:

    • The proposed CDSC strategy ensures semi-globally uniformly ultimately bounded signals in the closed-loop system.
    • The method effectively handles dynamic uncertainties and reduces signal transmission frequency.
    • Simulation results validate the effectiveness of the developed control strategy.

    Conclusions:

    • The NN-based CDSC strategy offers a robust solution for fixed-time formation control in nonlinear MASs.
    • The approach successfully balances performance requirements with communication limitations.
    • This work contributes to the advancement of coordinated control for MASs.