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

Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

334
Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
334
Determination of Multiple Dosing Parameters: Steady-State, Minimum and Maximum Concentrations01:15

Determination of Multiple Dosing Parameters: Steady-State, Minimum and Maximum Concentrations

228
Gentamicin, an aminoglycoside antibiotic, is commonly administered via intermittent intravenous infusion to treat severe infections. An intermittent one-hour infusion of gentamicin, administered at eight-hour intervals, allows for precise control of plasma drug concentrations, minimizing toxicity while ensuring therapeutic efficacy. Pharmacokinetic principles govern the dynamics of plasma concentrations and can be mathematically described using specific equations.The plasma drug concentration...
228
Optimization Problems01:26

Optimization Problems

8
Optimization problems often involve identifying maximum or minimum values under specific constraints. A well-known example is determining the longest horizontal pipe that can be moved around a right-angled corner, where a 3-meter-wide hallway meets a 2-meter-wide hallway. This scenario, common in architectural design and industrial transport, can be understood conceptually through geometric and trigonometric reasoning.To visualize the problem, consider the pipe as a straight line that touches...
8
Determination of Multiple Dosing Parameters: Loading and Maintenance Doses01:25

Determination of Multiple Dosing Parameters: Loading and Maintenance Doses

213
A loading dose is an essential pharmacological strategy to rapidly achieve the target plasma drug concentration necessary for an immediate therapeutic effect. This approach is especially critical for drugs characterized by slow absorption or extended half-lives, where delaying therapeutic plasma levels could compromise treatment outcomes. By administering a loading dose, clinicians ensure a prompt onset of drug action, even for agents with complex pharmacokinetic profiles.Achieving steady-state...
213
Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

1.1K
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...
1.1K
Parameters Affecting Nonlinear Elimination: Zero-Order Input, First-Order Absorption and Two-Compartment Model01:13

Parameters Affecting Nonlinear Elimination: Zero-Order Input, First-Order Absorption and Two-Compartment Model

281
Drugs administered through various routes can lead to nonlinear elimination, resulting in complex pharmacokinetic behaviors crucial to understanding efficacious drug dosing.
When a drug is administered through a constant intravenous infusion and eliminated via nonlinear pharmacokinetics, it follows zero-order input. For example, oral drugs undergo first-order absorption upon administration and are eliminated through nonlinear pharmacokinetics.
In the case of subcutaneously administered drugs,...
281

You might also read

Related Articles

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

Sort by
Same author

Mental health literacy predicts depression in older adults in China: an interpretable machine learning model.

The journals of gerontology. Series B, Psychological sciences and social sciences·2025
Same author

Time-Domain Attentional Biases in High Trait Anxiety: Insights From Event-Related Potentials in the RSVP Paradigm.

Psychophysiology·2025
Same author

Tumor-cell HLA-DR expression as a potential biomarker of immunotherapy response in hepatocellular carcinoma.

Frontiers in oncology·2025
Same author

Regulatory effects of Ophiopogon japonicus polysaccharide on intestinal immune function in mice.

International journal of biological macromolecules·2025
Same author

A scalable mental health intervention for depressive symptoms: evidence from a randomized controlled trial and large-scale real-world studies.

NPJ digital medicine·2025
Same author

A based <i>Cistanche deserticola</i> polysaccharide functional-nanoparticle delivery system for effective oral vaccine to facilitate both systemic and mucosal immunity through enhancing oral delivery.

Materials today. Bio·2025

Related Experiment Video

Updated: Jan 13, 2026

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
11:53

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

13.4K

Prescribed-time fully distributed optimization for time-varying costs: Zero-gradient-sum scheme.

Ningning Mao1, Shuai Liu1, Yuan Liu2

  • 1School of Control Science and Engineering, Shandong University, Jinan, 250061, China.

ISA Transactions
|January 11, 2026
PubMed
Summary
This summary is machine-generated.

This study presents a novel distributed optimization algorithm for time-varying objectives, achieving convergence within a user-defined deadline. The method uses adaptive parameters, eliminating the need for global network information for truly distributed control.

Keywords:
Adaptive controlFully distributed optimizationPrescribed-time convergenceTime-varying cost

More Related Videos

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

1.1K

Related Experiment Videos

Last Updated: Jan 13, 2026

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
11:53

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

13.4K
Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

1.1K

Area of Science:

  • Control Systems Engineering
  • Optimization Theory
  • Distributed Computing

Background:

  • Existing distributed optimization algorithms often require global network information or are limited by initial conditions.
  • Time-varying objectives pose challenges for convergence guarantees in distributed systems.

Purpose of the Study:

  • To develop a novel distributed optimization algorithm for time-varying objectives.
  • To achieve prescribed-time convergence without relying on global network information.
  • To overcome limitations of existing methods regarding initial conditions and network topology.

Main Methods:

  • Development of a distributed optimization algorithm based on zero-gradient-sum (ZGS) principles.
  • Implementation of a sliding-mode control framework with adaptive parameters and time-varying scaling functions.
  • Theoretical analysis combining optimization theory and Lyapunov stability analysis.

Main Results:

  • The algorithm achieves prescribed-time convergence for time-varying optimization problems.
  • It demonstrates true distributed control, independent of global network information and Laplacian eigenvalues.
  • The method is free from initial condition constraints and local minimization requirements.

Conclusions:

  • The proposed algorithm offers a robust and efficient solution for distributed optimization with time-varying objectives.
  • It significantly advances the field by enabling distributed control without global information.
  • Numerical simulations confirm its superior performance compared to existing approaches.