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

BIBO stability of continuous and discrete -time systems01:24

BIBO stability of continuous and discrete -time systems

986
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....
986
Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

1.2K
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...
1.2K
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

454
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 of...
454
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

375
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...
375
Linear time-invariant Systems01:23

Linear time-invariant Systems

1.0K
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...
1.0K
Differential Equations: Problem Solving01:21

Differential Equations: Problem Solving

102
When analyzing the motion of falling objects, it is essential to consider not only the force of gravity but also the opposing force of air resistance. A practical example involves releasing a heavy test weight during a safety check on a ship. As the weight falls from rest, gravity accelerates it downward while air resistance exerts an upward force that increases with velocity. This dynamic interplay of forces is well described by differential equations, which provide a mathematical framework...
102

You might also read

Related Articles

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

Sort by
Same author

Tea polyphenol-iron nanocapsules for oxalic acid-triggered delivery of n-butylidenephthalide: a biorational strategy against Sclerotium rolfsii.

Pest management science·2026
Same author

Predicting enhancer-promoter interactions using a stacking-based ensemble strategy.

Bioinformatics (Oxford, England)·2026
Same author

Mitochondrial ribosomal protein MRPL27 supports glioma malignancy through regulation of oxidative phosphorylation.

Cellular and molecular life sciences : CMLS·2026
Same author

Long non-coding RNA AC245100.4 for early diagnosis and prognostic assessment in acute pancreatitis: clinical value and inflammation-regulatory mechanisms.

Frontiers in pharmacology·2026
Same author

A Contrastive Free Energy-Enhanced Transformer Framework for Efficient Reinforcement Learning.

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

A Bayesian Stackelberg Game Approach to Remote State Estimation Under SINR-Based DoS Attacks with Incomplete Information.

Sensors (Basel, Switzerland)·2026
Same journal

A New Human-Likeness and Comfort Index for Robot Movements Along Prescribed Paths.

IEEE transactions on cybernetics·2026
Same journal

Robust Semiglobal and Global Stabilization for Nonlinear Normal Form Systems by Time-Varying Feedback.

IEEE transactions on cybernetics·2026
Same journal

Adaptive Global Asymptotic Output Stabilization of Uncertain Nonlinear Systems Under Dynamic State/Input Quantization.

IEEE transactions on cybernetics·2026
Same journal

Accelerated Distributed Gradient Tracking for Constrained Aggregative Optimization Over Time-Varying Digraphs.

IEEE transactions on cybernetics·2026
Same journal

Small-Gain-Based Plug-and-Play Distributed Control Framework for DC Microgrids With Decentralized Reconfiguration.

IEEE transactions on cybernetics·2026
Same journal

Prescribed-Time Impulsive Control of High-Order Integrator Systems.

IEEE transactions on cybernetics·2026
See all related articles

Related Experiment Videos

Distributed Optimization Design of Continuous-Time Multiagent Systems With Unknown-Frequency Disturbances.

Xinghu Wang, Yiguang Hong, Peng Yi

    IEEE Transactions on Cybernetics
    |May 26, 2017
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a distributed control method for multiagent systems facing unknown disturbances. The approach enables agents to reach optimal consensus while adapting to uncertain frequencies and rejecting external interference.

    Related Experiment Videos

    Area of Science:

    • Control Theory
    • Optimization
    • Multiagent Systems

    Background:

    • Distributed optimization problems are crucial for coordinating multiagent systems.
    • Continuous-time systems often face challenges from unknown-frequency disturbances.
    • Achieving optimal consensus requires robust control strategies.

    Purpose of the Study:

    • To develop a distributed gradient-based control for multiagent systems.
    • To address unknown-frequency disturbances and achieve optimal consensus.
    • To estimate unknown frequencies and reject bounded disturbances.

    Main Methods:

    • Convex optimization analysis.
    • Adaptive internal model approach.
    • Distributed gradient-based control design.

    Main Results:

    • The proposed control achieves optimal consensus in semi-global sense.
    • Unknown frequencies are estimated effectively.
    • Bounded disturbances with uncertain parameters are rejected.

    Conclusions:

    • The method provides an exact optimization solution for disturbed multiagent systems.
    • The adaptive internal model approach is effective for frequency estimation and disturbance rejection.
    • This work advances distributed control for complex dynamic systems.