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

Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

981
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...
981
Collisions in Multiple Dimensions: Problem Solving01:06

Collisions in Multiple Dimensions: Problem Solving

5.0K
In multiple dimensions, the conservation of momentum applies in each direction independently. Hence, to solve collisions in multiple dimensions, we should write down the momentum conservation in each direction separately. To help understand collisions in multiple dimensions, consider an example.
A small car of mass 1,200 kg traveling east at 60 km/h collides at an intersection with a truck of mass 3,000 kg traveling due north at 40 km/h. The two vehicles are locked together. What is the...
5.0K
Uniform Depth Channel Flow: Problem Solving01:18

Uniform Depth Channel Flow: Problem Solving

342
To calculate the flow rate for a trapezoidal channel, first, identify the bottom width, side slope, and flow depth of the channel. The cross-sectional area (A) corresponding to the depth of flow (y), channel bottom width (B), and side slope (θ) is determined by:Next, calculate the wetted perimeter, which includes the bottom width and the sloped side lengths in contact with the water. Using the values of the cross-sectional area and the wetted perimeter, determine the hydraulic radius by...
342
One-Degree-of-Freedom System01:24

One-Degree-of-Freedom System

698
In mechanical engineering, one-degree-of-freedom systems form the basis of a wide range of electrical and mechanical components. Using these models, engineers can predict the behavior of various parts in a larger system, which gives them insight into how different forces interact with each other.
A one-degree-of-freedom system is defined by an independent variable that determines its state and behavior. One example of a one-degree-of-freedom system is a simple harmonic oscillator, such as a...
698
Turbulent Flow: Problem Solving01:09

Turbulent Flow: Problem Solving

315
Carbonation is a process used to dissolve carbon dioxide gas in a liquid, commonly used in the production of carbonated beverages. Achieving efficient carbonation requires careful control of temperature, pressure, and flow conditions. By adjusting these parameters, carbonation efficiency can be maximized, producing a higher concentration of CO2 in the liquid.
Temperature is a key factor in CO2 solubility. In this case, the CO2 gas and the liquid are cooled to 20°C. Lower temperatures enhance...
315
Conservation of Momentum: Problem Solving01:30

Conservation of Momentum: Problem Solving

11.7K
Solving problems using the conservation of momentum requires four basic steps:
11.7K

You might also read

Related Articles

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

Sort by
Same author

Regulation of Arabidopsis thaliana plasma membrane glucose-responsive regulator (AtPGR) expression by A. thaliana storekeeper-like transcription factor, AtSTKL, modulates glucose response in Arabidopsis.

Plant physiology and biochemistry : PPB·2016
Same author

Astragaloside IV enhances diabetic wound healing involving upregulation of alternatively activated macrophages.

International immunopharmacology·2016
Same author

Interleukin-33 facilitates neutrophil recruitment and bacterial clearance in S. aureus-caused peritonitis.

Molecular immunology·2016
Same author

Plastic Deformation Modes of CuZr/Cu Multilayers.

Scientific reports·2016
Same author

The Effect of A2A Receptor Antagonist on Microglial Activation in Experimental Glaucoma.

Investigative ophthalmology & visual science·2016
Same author

A highly efficient degradation mechanism of methyl orange using Fe-based metallic glass powders.

Scientific reports·2016
Same journal

Stackelberg differential game-based fuzzy adaptive hierarchical optimal control for a nonlinear system with unknown dynamics.

ISA transactions·2026
Same journal

Composite fault-tolerant predictive control strategy for PMSM demagnetization faults.

ISA transactions·2026
Same journal

Bias-compensated Q-learning for optimal tracking control under denial-of-service attacks.

ISA transactions·2026
Same journal

Motion prediction for leader manipulator of teleoperation system with large time delay based on inverse optimal control.

ISA transactions·2026
Same journal

Neural network parameter identification-based prescribed-time adaptive control for morphing glide aircraft.

ISA transactions·2026
Same journal

Nonlinear system-guided continuous-time generalization for cross-aircraft engine state monitoring.

ISA transactions·2026
See all related articles

Related Experiment Video

Updated: Dec 12, 2025

Operation of the Collaborative Composite Manufacturing CCM System
10:09

Operation of the Collaborative Composite Manufacturing CCM System

Published on: October 1, 2019

6.9K

Distributed optimal consensus with obstacle avoidance algorithm of mixed-order UAVs-USVs-UUVs systems.

Xuekuan Yang1, Wei Wang1, Ping Huang1

  • 1College of Automation Harbin Engineering University, Harbin 150001, China.

ISA Transactions
|August 9, 2020
PubMed
Summary
This summary is machine-generated.

This study presents a distributed optimal control method for coordinating unmanned vehicles (UAVs, USVs, UUVs) in the ocean. The approach ensures stable formation control and effective obstacle avoidance for underwater vehicles.

Keywords:
ConsensusMixed-order multi-agent systems (MOMAS)Obstacle avoidanceOptimal formation control

More Related Videos

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

12.0K
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

13.3K

Related Experiment Videos

Last Updated: Dec 12, 2025

Operation of the Collaborative Composite Manufacturing CCM System
10:09

Operation of the Collaborative Composite Manufacturing CCM System

Published on: October 1, 2019

6.9K
The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

12.0K
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

13.3K

Area of Science:

  • Robotics
  • Control Systems
  • Ocean Engineering

Background:

  • Coordinating multiple unmanned vehicles (aerial, surface, underwater) presents significant challenges in complex ocean environments.
  • Existing formation control strategies often lack robustness for heterogeneous systems and integrated obstacle avoidance.

Purpose of the Study:

  • To develop a unified distributed optimal control strategy for formation control and obstacle avoidance in a mixed-order linear multi-agent system.
  • To enhance the operational safety and efficiency of unmanned systems in marine applications.

Main Methods:

  • A consensus control law was designed for horizontal and height directions, ensuring stability using block Kronecker product and matrix transformation theory.
  • A linear quadratic regulator method was implemented for distributed optimization.
  • An inverse optimal control approach with a non-quadratic penalty function was used for obstacle avoidance in unmanned underwater vehicles, considering seamount threats.

Main Results:

  • The proposed distributed optimal control approach successfully achieved consensus control for the multi-agent system.
  • The integrated strategy demonstrated effective obstacle avoidance capabilities for unmanned underwater vehicles.
  • Simulation results validated the efficiency and stability of the formation control and obstacle avoidance mechanisms.

Conclusions:

  • The developed distributed optimal control framework provides a robust solution for coordinated control of mixed-order unmanned systems in ocean environments.
  • The method effectively integrates formation control with sophisticated obstacle avoidance, paving the way for safer and more autonomous marine operations.