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

Multimachine Stability01:25

Multimachine Stability

242
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:
242
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

180
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...
180
Hierarchy of Motor Control01:18

Hierarchy of Motor Control

3.8K
The hierarchy of motor control refers to the different levels of organization and processing involved in controlling movement in the body. These levels range from higher cortical areas involved in planning and decision-making to lower spinal cord reflexes that respond automatically to external stimuli.
3.8K
Neural Circuits01:25

Neural Circuits

1.7K
Neural circuits and neuronal pools are two of the main structures found in the nervous system. Neural circuits are networks of neurons that work together to carry out a specific task or process. They consist of interconnected neurons and glial cells, which provide structural and metabolic support.
Neuronal pools are collections of nerve cells with similar functions and interact through chemical and electrical signals. These pools include both interneurons (the central neural circuit nodes that...
1.7K
Neural Regulation01:37

Neural Regulation

40.4K
Digestion begins with a cephalic phase that prepares the digestive system to receive food. When our brain processes visual or olfactory information about food, it triggers impulses in the cranial nerves innervating the salivary glands and stomach to prepare for food.
40.4K
Open and closed-loop control systems01:17

Open and closed-loop control systems

1.1K
Control systems are foundational elements in automation and engineering. They are broadly categorized into open-loop and closed-loop systems. These classifications hinge on the presence or absence of feedback mechanisms, significantly influencing the system's performance, complexity, and application.
An open-loop control system operates without feedback from the output. It consists of two primary elements: the controller and the controlled process. The controller receives an input signal...
1.1K

You might also read

Related Articles

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

Sort by
Same author

Event-Based Integral Sliding-Mode Consensus Control for Networked Multiagent Systems With State Quantization.

IEEE transactions on cybernetics·2025
Same author

Adaptive Event-Triggered Sliding-Mode Control for Consensus Tracking of Nonlinear Multiagent Systems With Unknown Perturbations.

IEEE transactions on cybernetics·2022
Same author

Event-Based Finite-Time Neural Control for Human-in-the-Loop UAV Attitude Systems.

IEEE transactions on neural networks and learning systems·2022
Same author

Secure Finite-Horizon Consensus Control of Multiagent Systems Against Cyber Attacks.

IEEE transactions on cybernetics·2021
Same author

Distributed Cooperative Compound Tracking Control for a Platoon of Vehicles With Adaptive NN.

IEEE transactions on cybernetics·2021
Same author

Cadmium accumulation in oilseed rape is promoted by intercropping with faba bean and ryegrass.

Ecotoxicology and environmental safety·2020

Related Experiment Video

Updated: Sep 28, 2025

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

641

Bounded Antisynchronization of Multiple Neural Networks via Multilevel Hybrid Control.

Fen Liu, Wei Meng, Deyin Yao

    IEEE Transactions on Neural Networks and Learning Systems
    |March 31, 2022
    PubMed
    Summary
    This summary is machine-generated.

    This study addresses bounded antisynchronization in fuzzy neural networks using a novel cluster pinning mechanism and an impulsive observer. These methods ensure energy-efficient communication and robust state estimation for complex network dynamics.

    More Related Videos

    Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
    11:18

    Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

    Published on: March 2, 2015

    10.5K
    Automated Multimodal Stimulation and Simultaneous Neuronal Recording from Multiple Small Organisms
    08:28

    Automated Multimodal Stimulation and Simultaneous Neuronal Recording from Multiple Small Organisms

    Published on: March 3, 2023

    1.2K

    Related Experiment Videos

    Last Updated: Sep 28, 2025

    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

    641
    Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
    11:18

    Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

    Published on: March 2, 2015

    10.5K
    Automated Multimodal Stimulation and Simultaneous Neuronal Recording from Multiple Small Organisms
    08:28

    Automated Multimodal Stimulation and Simultaneous Neuronal Recording from Multiple Small Organisms

    Published on: March 3, 2023

    1.2K

    Area of Science:

    • Control Theory
    • Artificial Intelligence
    • Network Science

    Background:

    • Investigates the bounded antisynchronization (AS) problem in multiple discrete-time neural networks (NNs) with fuzzy models.
    • Addresses challenges posed by varying group sizes, communication links, dynamic variabilities, and environmental factors affecting network topology.

    Purpose of the Study:

    • To propose an energy-efficient cluster pinning communication mechanism for multiple NNs.
    • To design an impulsive observer for accurate state estimation of target NNs.
    • To develop a multilevel hybrid controller integrating AS and bounded synchronization (BS) controllers.

    Main Methods:

    • A cluster pinning communication mechanism is introduced to minimize communication energy consumption.
    • An impulsive observer is designed for state estimation of the target NN.
    • Stability analysis of the BS augmented error (BSAE) and AS augmented error (ASAE) using a fuzzy-based Lyapunov functional (FBLF) establishes sufficient conditions for bounded AS.

    Main Results:

    • Sufficient conditions for achieving bounded antisynchronization in the considered fuzzy neural network systems are derived.
    • The proposed cluster pinning mechanism and impulsive observer effectively manage communication and state estimation.
    • The multilevel hybrid controller demonstrates capability in achieving bounded AS.

    Conclusions:

    • The study successfully establishes conditions for bounded antisynchronization in complex fuzzy neural network systems.
    • The developed methods offer a viable approach for energy-efficient control and state estimation in distributed NN systems.
    • Numerical and application examples validate the effectiveness of the proposed theoretical framework.