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

Open and closed-loop control systems01:17

Open and closed-loop control systems

597
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...
597
Woodward–Hoffmann Selection Rules and Microscopic Reversibility01:34

Woodward–Hoffmann Selection Rules and Microscopic Reversibility

3.0K
Electrocyclic reactions, cycloadditions, and sigmatropic rearrangements are concerted pericyclic reactions that proceed via a cyclic transition state. These reactions are stereospecific and regioselective. The stereochemistry of the products depends on the symmetry characteristics of the interacting orbitals and the reaction conditions. Accordingly, pericyclic reactions are classified as either symmetry-allowed or symmetry-forbidden. Woodward and Hoffmann presented the selection criteria for...
3.0K
Stability of Equilibrium Configuration: Problem Solving01:13

Stability of Equilibrium Configuration: Problem Solving

561
The stability of equilibrium configurations is an important concept in physics, engineering, and other related fields. In simple terms, it refers to the tendency of an object or system to return to its equilibrium position after being disturbed. The stability of an equilibrium configuration can be analyzed by considering the potential energy function of the system and examining its behavior near the equilibrium point.
Problem-solving in the context of the stability of equilibrium configuration...
561
Feedback control systems01:26

Feedback control systems

264
Feedback control systems are categorized in various ways based on their design, analysis, and signal types.
Linear feedback systems are theoretical models that simplify analysis and design. These systems operate under the principle that their output is directly proportional to their input within certain ranges. For instance, an amplifier in a control system behaves linearly as long as the input signal remains within a specific range. However, most physical systems exhibit inherent nonlinearity...
264
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

93
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...
93
Statically Indeterminate Problem Solving01:16

Statically Indeterminate Problem Solving

350
Statically indeterminate problems are those where statics alone can not determine the internal forces or reactions. Consider a structure comprising two cylindrical rods made of steel and brass. These rods are joined at point B and restrained by rigid supports at points A and C. Now, the reactions at points A and C and the deflection at point B are to be determined. This rod structure is classified as statically indeterminate as the structure has more supports than are necessary for maintaining...
350

You might also read

Related Articles

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

Sort by
Same author

Stochastic Event-Triggered Fault Detection and Isolation Based on Kalman Filter.

IEEE transactions on cybernetics·2021
Same author

A new approach for robust fault estimation in nonlinear systems with state-coupled disturbances using dissipativity theory.

ISA transactions·2021
See all related articles

Related Experiment Video

Updated: May 22, 2025

WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control
08:18

WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control

Published on: August 15, 2020

4.9K

Data-Driven Inverse Reinforcement Learning for Heterogeneous Optimal Robust Formation Control.

Fatemeh Mahdavi Golmisheh, Saeed Shamaghdari

    IEEE Transactions on Cybernetics
    |March 14, 2025
    PubMed
    Summary

    This study introduces data-driven inverse reinforcement learning (IRL) algorithms for multiagent systems (MASs) to achieve optimal formation control despite disturbances. The methods ensure stability and convergence for complex MAS tasks.

    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

    11.5K
    Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
    11:54

    Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

    Published on: May 8, 2021

    4.3K

    Related Experiment Videos

    Last Updated: May 22, 2025

    WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control
    08:18

    WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control

    Published on: August 15, 2020

    4.9K
    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

    11.5K
    Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
    11:54

    Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

    Published on: May 8, 2021

    4.3K

    Area of Science:

    • Robotics
    • Artificial Intelligence
    • Control Systems

    Background:

    • Heterogeneous formation control in multiagent systems (MASs) presents challenges due to complex dynamics and external disturbances.
    • Identifying unknown reward functions and optimal control policies is crucial for MAS performance.
    • Existing methods often require full knowledge of system dynamics, limiting their applicability.

    Purpose of the Study:

    • To develop novel data-driven inverse reinforcement learning (IRL) algorithms for optimal formation control in MASs.
    • To address heterogeneous formation control problems under disturbance conditions.
    • To enable MASs to learn optimal behaviors from expert demonstrations without prior knowledge of their dynamics.

    Main Methods:

    • Proposed expert-estimator-learner MAS architecture with similar interaction graphs.
    • Developed a model-based IRL algorithm for the estimator MAS to derive optimal control and reward functions.
    • Introduced a robust model-free IRL algorithm for the learner MAS, leveraging estimator results without needing learner dynamics.
    • Presented data-driven implementations of the proposed IRL algorithms.

    Main Results:

    • Successfully reconstructed optimal control and reward functions for both estimator and learner MASs.
    • Demonstrated the ability to identify unknown reward functions and optimal controls through demonstrations.
    • Validated the stability and convergence of the multiagent systems using theoretical analysis.
    • Confirmed the effectiveness of the proposed algorithms through simulation results.

    Conclusions:

    • The developed data-driven IRL algorithms effectively address heterogeneous formation control in MASs under disturbances.
    • The expert-estimator-learner framework enables learning optimal policies even without complete knowledge of system dynamics.
    • The research contributes a robust methodology for reward function identification and optimal control in MASs.