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

Root-Locus Method01:19

Root-Locus Method

448
A cruise control system in a car is designed to maintain a specified speed automatically by adjusting the gas pedal. The system continuously measures the vehicle's speed and makes fine adjustments to the pedal to achieve this goal. The root locus method is particularly useful for understanding how the cruise control system's behavior changes under varying conditions, such as when the car goes uphill, downhill, or faces strong wind resistance.
This system can be represented by a block...
448
Absolute Motion Analysis- General Plane Motion01:24

Absolute Motion Analysis- General Plane Motion

508
Visualize a drone, with its propellers spinning rapidly, hovering mid-air. The fascinating movements and operations of this drone can be comprehended by applying the principle of general plane motion.
As the drone's propellers rotate, an upward force is generated that counteracts the force of gravity, enabling the drone to lift off from the ground. This initial movement of the drone is along a straight path, representing a form of translational motion. In this phase, every point on the...
508
Direct Motor Pathways01:11

Direct Motor Pathways

4.1K
The direct motor pathways, also known as the pyramidal tracts, are a group of neural pathways that originate in the brain and descend through the spinal cord. They control the voluntary movement of the body. There are two major direct motor pathways: the corticospinal and the corticobulbar tracts.
The corticospinal tract is responsible for the voluntary movement of the limbs and trunk. It originates in the cerebral cortex of the brain and descends through the cerebrum's internal capsule and...
4.1K
Rolling Resistance: Problem Solving01:17

Rolling Resistance: Problem Solving

766
Rolling resistance, also known as rolling friction, is the force that resists the motion of a rolling object, such as a wheel, tire, or ball, when it moves over a surface. It is caused by the deformation of the object and the surface in contact with each other, as well as other factors like internal friction, hysteresis, and energy losses within the materials. Rolling resistance opposes the object's motion, requiring additional energy to overcome it and maintain movement. In practical...
766
One-Degree-of-Freedom System01:24

One-Degree-of-Freedom System

777
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...
777
Open and closed-loop control systems01:17

Open and closed-loop control systems

1.5K
Control systems are foundational elements in automation and engineering. They are broadly categorized into open-loop and closed-loop systems. These classifications hinge on the presence or absence of feedback mechanisms, significantly influencing the system's performance, complexity, and application.
An open-loop control system operates without feedback from the output. It consists of two primary elements: the controller and the controlled process. The controller receives an input signal...
1.5K

You might also read

Related Articles

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

Sort by
Same author

A pilot study on microbial dynamics in drainage fluid during trauma recovery.

Annals of surgical treatment and research·2026
Same author

Protecting cells at the genetic level and simulating unauthorized access via a biohackathon.

Science advances·2026
Same author

Microbiological Profiles of Surgical Pad Cultures in Damage Control Surgery: Clinical Implications and Predictive Factors.

Surgical infections·2025
Same author

Endotoxin Pretreatment Mitigates Myocardial Ischemia-Reperfusion Injury Through Preservation of Mitochondrial Respiration: A Combined Assessment of In Vivo, Ex Vivo, and In Vitro Data.

International journal of molecular sciences·2025
Same author

Development of predictive and evaluation models for the retro reflectivity performance of pavement lane markings.

F1000Research·2025
Same author

From progress to precision: a decadal reassessment of national particulate matter footprint across industries and regions.

Environmental science and pollution research international·2025

Related Experiment Video

Updated: Jan 9, 2026

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

12.1K

Data-driven path-following control for unmanned surface vehicles.

Je Wook Ryu1, Seunghwan Han2, Dowan Kim3

  • 1Department of Ocean Systems Engineering, Sejong University, Seoul, 05006, South Korea.

Scientific Reports
|December 9, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a data-driven control method for unmanned surface vehicles (USVs) using linear matrix inequalities (LMIs). The approach ensures robust path following despite partially unknown vehicle dynamics.

Keywords:
Asymptotic stabilityData-driven controlLinear matrix inequality (LMI)LyapunovPath-followingUnmanned surface vehicles (USV)

More Related Videos

A Real-Time Interactive System for Studying Confrontational Pursuit Behavior in Rodents
06:25

A Real-Time Interactive System for Studying Confrontational Pursuit Behavior in Rodents

Published on: May 16, 2025

1.3K
Insect-controlled Robot: A Mobile Robot Platform to Evaluate the Odor-tracking Capability of an Insect
09:00

Insect-controlled Robot: A Mobile Robot Platform to Evaluate the Odor-tracking Capability of an Insect

Published on: December 19, 2016

15.1K

Related Experiment Videos

Last Updated: Jan 9, 2026

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

12.1K
A Real-Time Interactive System for Studying Confrontational Pursuit Behavior in Rodents
06:25

A Real-Time Interactive System for Studying Confrontational Pursuit Behavior in Rodents

Published on: May 16, 2025

1.3K
Insect-controlled Robot: A Mobile Robot Platform to Evaluate the Odor-tracking Capability of an Insect
09:00

Insect-controlled Robot: A Mobile Robot Platform to Evaluate the Odor-tracking Capability of an Insect

Published on: December 19, 2016

15.1K

Area of Science:

  • Robotics and Control Systems
  • Marine Engineering
  • Systems and Control Theory

Background:

  • Unmanned Surface Vehicles (USVs) require advanced control for autonomous navigation.
  • Partially unknown dynamics pose significant challenges for robust path following.
  • Data-driven control offers a promising alternative to traditional model-based approaches.

Purpose of the Study:

  • To develop a data-driven control formulation for USV path following.
  • To address challenges posed by partially unknown system dynamics.
  • To guarantee robust asymptotic stability using linear matrix inequalities (LMIs).

Main Methods:

  • Decomposition of the USV system into known and partially unknown subsystems.
  • Constraining unknown dynamics within a data-consistent, matrix-ellipsoidal uncertainty set.
  • Derivation of sufficient stability conditions using LMIs based on input-state measurements.

Main Results:

  • A novel formulation for data-driven path following control of USVs is presented.
  • Robust asymptotic stability is guaranteed under matrix-ellipsoidal uncertainty.
  • The data-driven controller demonstrates performance comparable to model-based methods.

Conclusions:

  • The proposed LMI-based data-driven control effectively handles partially unknown USV dynamics.
  • This method provides a robust solution for autonomous USV path following.
  • The approach achieves high performance across various reference paths.