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

Distributed Loads: Problem Solving

Distributed Loads: Problem Solving

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...

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...

BIBO stability of continuous and discrete -time systems

BIBO stability of continuous and discrete -time systems

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....

Linear time-invariant Systems

Linear time-invariant Systems

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...

Basic Continuous Time Signals

Basic Continuous Time Signals

Basic continuous-time signals include the unit step function, unit impulse function, and unit ramp function, collectively referred to as singularity functions. Singularity functions are characterized by discontinuities or discontinuous derivatives.
The unit step function, denoted u(t), is zero for negative time values and one for positive time values, exhibiting a discontinuity at t=0. This function often represents abrupt changes, such as the step voltage introduced when turning a car's...

Second Order systems I

Second Order systems I

A servo system exemplifies a second-order system, featuring a proportional controller and load elements that ensure the output position aligns with the input position. The relationship between these components is described by a second-order differential equation. Applying the Laplace transform under zero initial conditions yields the transfer function, showing how inputs are converted to outputs in the system.
By reinterpreting the system, one can derive the closed-loop transfer function, which...

You might also read

Related Articles

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

Sort by

Same author

Controlled analog Ising machine: An accelerated and accuracy-enhanced intelligent solver for edge computing.

Innovation (Cambridge (Mass.))·2026

Same author

HyperSAT: Unsupervised Hypergraph Neural Networks for Weighted MaxSAT Problems.

IEEE transactions on neural networks and learning systems·2026

Same author

Deep learning-enhanced prescribed-time cooperative guidance with switching topologies under time-varying velocity.

ISA transactions·2026

Same author

Application of multimodal nanotechnology and standardized nursing management in ventricular arrhythmia.

Biomedical engineering online·2026

Same author

Distributed Output Formation Optimal Tracking of Heterogeneous Linear Multiagent Systems via Distributed Time-Varying Optimization.

IEEE transactions on cybernetics·2026

Same author

Pursuit Strategies for Capture-the-Flag Games With Half-Plane Flag and Return Region.

IEEE transactions on cybernetics·2026

Search research articles

Related Experiment Video

Updated: Jun 14, 2025

A Protocol for Real-time 3D Single Particle Tracking

A Protocol for Real-time 3D Single Particle Tracking

Published on: January 3, 2018

Distributed Asynchronous Constrained Output Formation Optimal Tracking for Multiagent Systems With Intermittent

Lingfei Su, Yongzhao Hua, Xiwang Dong

IEEE Transactions on Cybernetics

|September 4, 2024

Summary

This summary is machine-generated.

This study addresses optimal tracking for multiagent systems with unreliable communications. Agents achieve consensus on optimal formation control despite asynchronous and intermittent communication, ensuring stability and convergence.

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

The HoneyComb Paradigm for Research on Collective Human Behavior

The HoneyComb Paradigm for Research on Collective Human Behavior

Published on: January 19, 2019

Related Experiment Videos

Last Updated: Jun 14, 2025

A Protocol for Real-time 3D Single Particle Tracking

A Protocol for Real-time 3D Single Particle Tracking

Published on: January 3, 2018

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

The HoneyComb Paradigm for Research on Collective Human Behavior

The HoneyComb Paradigm for Research on Collective Human Behavior

Published on: January 19, 2019

Area of Science:

Control Systems Engineering
Distributed Systems
Optimization Theory

Background:

Multiagent systems face challenges in achieving coordinated control under dynamic and unreliable communication networks.
Optimal formation tracking requires agents to simultaneously satisfy individual objectives and global constraints.

Purpose of the Study:

To investigate distributed output formation optimal tracking for multiagent systems with time-varying topologies and asynchronous, intermittent communications.
To develop a control protocol ensuring agents converge to an optimal reference signal.

Main Methods:

Designed an asynchronous distributed estimator-based tracking control protocol.
Utilized constrained stochastic subgradient random projection and Lyapunov stability theory.
Established sufficient conditions for asymptotic convergence.

Main Results:

Agents collaboratively compute and track an optimal output formation reference minimizing a global objective function.
The optimal reference satisfies global constraints, including local nonlinear inequalities and closed convex sets.
Demonstrated asymptotic convergence of constrained agent states to the optimal reference using only local information.

Conclusions:

The proposed control protocol effectively achieves optimal formation tracking in multiagent systems under challenging communication conditions.
Theoretical results are validated through a numerical example, confirming the robustness and applicability of the approach.