Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Multi-input and Multi-variable systems

Multi-input and Multi-variable systems

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...

Feedback control systems

Feedback control systems

Feedback control systems are categorized in various ways based on their design, analysis, and signal types.
Linear feedback systems are theoretical models that simplify analysis and design. These systems operate under the principle that their output is directly proportional to their input within certain ranges. For instance, an amplifier in a control system behaves linearly as long as the input signal remains within a specific range. However, most physical systems exhibit inherent nonlinearity...

Elastic Collisions: Case Study

Elastic Collisions: Case Study

Elastic collision of a system demands conservation of both momentum and kinetic energy. To solve problems involving one-dimensional elastic collisions between two objects, the equations for conservation of momentum and conservation of internal kinetic energy can be used. For the two objects, the sum of momentum before the collision equals the total momentum after the collision. An elastic collision conserves internal kinetic energy, and so the sum of kinetic energies before the collision equals...

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...

Control Systems

Control Systems

Control systems are everywhere in contemporary society, influencing diverse applications from aerospace to automated manufacturing. These systems can be found naturally within biological processes, such as blood sugar regulation and heart rate adjustment in response to stress, as well as in man-made systems like elevators and automated vehicles. A control system is essentially a network of subsystems and processes that collaboratively convert specific inputs into desired outputs.
At the heart...

Masking and Demasking Agents

Masking and Demasking Agents

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...

You might also read

Related Articles

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

Sort by

Same author

Multi-scaling reservoir computing learns noise-induced transitions with Lévy noise.

Chaos (Woodbury, N.Y.)·2025

Same author

Early warnings are too late when parameters change rapidly.

Scientific reports·2025

Same author

Nonmonotonic emergence of order from chaos in turbulent thermoacoustic fluid systems.

Physical review. E·2025

Same author

Dynamic Evolution of Complex Networks: A Reinforcement Learning Approach Applying Evolutionary Games to Community Structure.

IEEE transactions on pattern analysis and machine intelligence·2025

Same author

The circular movement of synchronous extreme precipitation preceding Kerala floods in 2018 and 2019.

Chaos (Woodbury, N.Y.)·2025

Same author

Extreme events in two coupled chaotic oscillators.

Physical review. E·2025

Search research articles

Related Experiment Video

Updated: Aug 4, 2025

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

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

Published on: August 15, 2020

Event-Triggered Adaptive Containment Control for Heterogeneous Stochastic Nonlinear Multiagent Systems.

Xin Wang, Rui Xu, Tingwen Huang

IEEE Transactions on Neural Networks and Learning Systems

|April 5, 2023

Summary

This summary is machine-generated.

This study presents an event-triggered adaptive containment control for stochastic nonlinear multiagent systems. It ensures follower convergence to leader convex hulls while minimizing communication using neural networks and observers.

More Related Videos

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

Published on: May 8, 2021

A Modified Lean and Release Technique to Emphasize Response Inhibition and Action Selection in Reactive Balance

A Modified Lean and Release Technique to Emphasize Response Inhibition and Action Selection in Reactive Balance

Published on: March 19, 2020

Related Experiment Videos

Last Updated: Aug 4, 2025

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

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

Published on: August 15, 2020

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

Published on: May 8, 2021

A Modified Lean and Release Technique to Emphasize Response Inhibition and Action Selection in Reactive Balance

A Modified Lean and Release Technique to Emphasize Response Inhibition and Action Selection in Reactive Balance

Published on: March 19, 2020

Area of Science:

Control Theory
Nonlinear Systems
Stochastic Systems

Background:

Multiagent systems (MAS) are crucial for distributed tasks.
Stochastic nonlinear systems with unmeasurable states present control challenges.
Event-triggered control aims to reduce communication load in MAS.

Purpose of the Study:

To develop an event-triggered adaptive containment control strategy.
To address stochastic nonlinear multiagent systems with unmeasurable states.
To reduce communication costs while maintaining system performance.

Main Methods:

Approximation of uncertain nonlinear dynamics using radial basis function neural networks (NNs).
Design of NN-based observers for estimating unmeasured states.
Implementation of a switching-threshold-based event-triggered control mechanism.
Application of adaptive backstepping and dynamic surface control (DSC) for controller design.

Main Results:

The proposed controller ensures follower outputs converge to the convex hull of leaders.
All signals in the closed-loop system are cooperatively semi-globally uniformly ultimately bounded in mean square.
The event-triggered approach effectively reduces communication consumption.

Conclusions:

The developed event-triggered adaptive containment control is effective for stochastic nonlinear multiagent systems.
The combination of NNs, observers, and adaptive control strategies achieves desired containment performance.
The proposed method offers a practical solution for resource-constrained networked systems.