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

Vector Functions and Motion: Problem Solving01:30

Vector Functions and Motion: Problem Solving

Accurate position tracking is fundamental to the safe and effective operation of unmanned aerial vehicles (UAVs), particularly during precision maneuvers near complex structures. In this scenario, a drone is programmed to perform a high-precision inspection of a vertical structure, starting at position ((x, y, z) = (3, 0, 0)), with an initial velocity oriented in the positive z-direction. The trajectory of the drone is governed by a time-dependent acceleration function a(t), which is predefined...
Real-World Applications of Space Curves01:29

Real-World Applications of Space Curves

Modern aerospace navigation depends on the accurate prediction of motion in three-dimensional space. In defense applications, radar systems continuously track both interceptors and moving aerial targets to find whether their flight paths will result in a collision. These motions are modeled mathematically as space curves, which represent paths that change continuously with time. Each object’s position is described by a vector function that specifies its location in terms of time-dependent...
Multi-input and Multi-variable systems01:22

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 of...
Buoyancy and Stability for Submerged and Floating Bodies01:11

Buoyancy and Stability for Submerged and Floating Bodies

In fluid mechanics, buoyancy and stability are key concepts for understanding the behavior of submerged and floating bodies. When a stationary body is fully or partially submerged in a fluid, the fluid exerts a force on the body known as the buoyant force. This force acts vertically upward through a point called the center of buoyancy, which is the center of the displaced fluid volume. According to Archimedes' principle, the magnitude of the buoyant force is equal to the weight of the fluid...
Controller Configurations01:22

Controller Configurations

Controller configurations are crucial in a car's cruise control system because they manage speed over time to maintain a consistent pace regardless of road conditions, thereby meeting design goals. In traditional control systems, fixed-configuration design involves predetermined controller placement. System performance modifications are known as compensation.
Control-system compensation involves various configurations, most commonly series or cascade compensation, in which the controller aligns...
Uniform Depth Channel Flow: Problem Solving01:18

Uniform Depth Channel Flow: Problem Solving

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...

You might also read

Related Articles

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

Sort by
Same author

Reinforcement learning-based optimal formation control of underactuated USVs with prescribed performance under communication delays.

ISA transactions·2026
Same author

Integrating machine learning and metabolomics to identify PFAS-associated metabolic alterations related to lung cancer risk.

Environment international·2026
Same author

Corrigendum to "Identification and functional characterization of SmABCG24 regulating tanshinone transport in Salvia miltiorrhiza" [Int. J. Biol. Macromol. 360 (2026) 151837].

International journal of biological macromolecules·2026
Same author

Effects of constant and incremental modes of music volume and odor concentration on vigilance.

Frontiers in psychology·2026
Same author

Identification and functional characterization of SmABCG24 regulating tanshinone transport in Salvia miltiorrhiza.

International journal of biological macromolecules·2026
Same author

Dimensionality-Mixed Phases Facilitate Chirality Transfer and Spin-Orbit Coupling for Chiral Perovskite Red Spin-LEDs.

ACS nano·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
Same journal

Predefined-time distributed optimal formation control for constrained UAV-UGV systems.

ISA transactions·2026
Same journal

Fixed-time distributed secondary control for voltage/frequency restoration and power sharing in microgrids under switching topologies.

ISA transactions·2026
Same journal

A robust ATUB-Net for bearing fault diagnosis under unbalanced sample scenarios.

ISA transactions·2026
Same journal

Data-driven trajectory tracking control of UAV systems under a novel probability-selection event-triggered mechanism.

ISA transactions·2026
See all related articles

Related Experiment Videos

Discrete-time distributed model predictive control-based collision-avoidance formation tracking control for multiple

Haomiao Yu1, Yue Wang1

  • 1College of Marine Electrical Engineering, Dalian Maritime University, Dalian 116026, People's Republic of China.

ISA Transactions
|June 20, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces a robust discrete-time control architecture for unmanned underwater vehicles (UUVs), enabling precise trajectory tracking and obstacle avoidance despite system delays. The dual-loop design ensures stability and efficiency in complex underwater environments.

Keywords:
Discrete sliding mode controlDiscrete-time formation controlDistributed model predictive controlObstacle avoidanceUnmanned underwater vehicle

Related Experiment Videos

Area of Science:

  • Robotics
  • Control Systems Engineering
  • Marine Technology

Background:

  • Unmanned underwater vehicles (UUVs) require simultaneous trajectory tracking and obstacle avoidance.
  • Digital implementation introduces discretization errors and time delays, degrading continuous-time control methods.
  • High-precision control in discrete-time systems remains a significant challenge.

Purpose of the Study:

  • To develop a robust discrete-time dual-loop control architecture for UUVs.
  • To address performance degradation issues in discrete-time implementations of control systems.
  • To achieve high-precision trajectory tracking and reliable obstacle avoidance in UUVs.

Main Methods:

  • A discrete-time distributed model predictive control (DMPC) outer-loop generates collision-free velocity commands with LQR-based terminal constraints and slack variables.
  • A discrete-time sliding mode controller (DSMC) with a specialized reaching law forms the inner dynamic loop.
  • A discrete disturbance observer (DDOB) estimates and compensates for ocean current disturbances.

Main Results:

  • The proposed framework demonstrates superior tracking accuracy and computational efficiency.
  • Reliable obstacle avoidance capabilities were achieved in simulations.
  • The dual-loop architecture ensures global system stability under discrete-time constraints.

Conclusions:

  • The robust discrete-time dual-loop control architecture effectively addresses challenges in UUV control.
  • The method provides a stable and efficient solution for simultaneous trajectory tracking and obstacle avoidance.
  • This approach enhances UUV performance in complex, dynamic underwater environments.