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

Feedback control systems01:26

Feedback control systems

610
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...
610
BIBO stability of continuous and discrete -time systems01:24

BIBO stability of continuous and discrete -time systems

820
System stability is a fundamental concept in signal processing, often assessed using convolution. For a system to be considered bounded-input bounded-output (BIBO) stable, any bounded input signal must produce a bounded output signal. A bounded input signal is one where the modulus does not exceed a certain constant at any point in time.
To determine the BIBO stability, the convolution integral is utilized when a bounded continuous-time input is applied to a Linear Time-Invariant (LTI) system....
820
Time-Domain Interpretation of PD Control01:07

Time-Domain Interpretation of PD Control

299
Proportional-Derivative (PD) control is a widely used control method in various engineering systems to enhance stability and performance. In a system with only proportional control, common issues include high maximum overshoot and oscillation, observed in both the error signal and its rate of change. This behavior can be divided into three distinct phases: initial overshoot, subsequent undershoot, and gradual stabilization.
Consider the example of control of motor torque. Initially, a positive...
299
Transient and Steady-state Response01:24

Transient and Steady-state Response

447
In control systems, test signals are essential for evaluating performance under various conditions. The ramp function is effective for systems undergoing gradual changes, while the step function is suitable for assessing systems facing sudden disturbances. For systems subjected to shock inputs, the impulse function is the most appropriate test signal.
These test signals are integral in designing control systems to exhibit two key performance aspects: transient response and steady-state...
447
Stability01:28

Stability

300
The time response of a linear time-invariant (LTI) system can be divided into transient and steady-state responses. The transient response represents the system's initial reaction to a change in input and diminishes to zero over time. In contrast, the steady-state response is the behavior that persists after the transient effects have faded.
The stability of an LTI system is determined by the roots of its characteristic equation, known as poles. A system is stable if it produces a bounded...
300
Control Systems01:10

Control Systems

1.7K
Control systems are everywhere in contemporary society, influencing diverse applications from aerospace to automated manufacturing. These systems can be found naturally within biological processes, such as blood sugar regulation and heart rate adjustment in response to stress, as well as in man-made systems like elevators and automated vehicles. A control system is essentially a network of subsystems and processes that collaboratively convert specific inputs into desired outputs.
At the heart...
1.7K

You might also read

Related Articles

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

Sort by
Same author

Learning multi-regularized mutation-aware correlation filter for object tracking via an adaptive hybrid model.

Neural networks : the official journal of the International Neural Network Society·2025
Same author

Markov Switching Topology-Based Reliable Control Design for Delayed Discrete-Time System: An Ellipsoidal Attracting Approach.

IEEE transactions on cybernetics·2025
Same author

Learning temporal regularized spatial-aware deep correlation filter tracking via adaptive channel selection.

Neural networks : the official journal of the International Neural Network Society·2025
Same author

Epidemiological surveillance and phylogenetic diversity of Orthohantavirus hantanense using high-fidelity nanopore sequencing, Republic of Korea.

PLoS neglected tropical diseases·2025
Same author

An improved model predictive control of back-to-back three-level NPC converters with virtual space vectors for high power PMSG-based wind energy conversion systems.

ISA transactions·2023
Same author

Learning dynamic spatial-temporal regularized correlation filter tracking with response deviation suppression via multi-feature fusion.

Neural networks : the official journal of the International Neural Network Society·2023

Related Experiment Video

Updated: Dec 17, 2025

Interactive and Visualized Online Experimentation System for Engineering Education and Research
08:35

Interactive and Visualized Online Experimentation System for Engineering Education and Research

Published on: November 24, 2021

2.9K

Stabilization of Interval Type-2 Fuzzy-Based Reliable Sampled-Data Control Systems.

Subramanian Kuppusamy, Young Hoon Joo

    IEEE Transactions on Cybernetics
    |July 1, 2020
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a novel reliable sampled-data control for interval type-2 Takagi-Sugeno fuzzy systems. The method ensures global asymptotic stability using advanced Lyapunov-Krasovskii functionals and linear matrix inequalities.

    More Related Videos

    Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
    06:45

    Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

    Published on: October 28, 2022

    2.0K
    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

    5.3K

    Related Experiment Videos

    Last Updated: Dec 17, 2025

    Interactive and Visualized Online Experimentation System for Engineering Education and Research
    08:35

    Interactive and Visualized Online Experimentation System for Engineering Education and Research

    Published on: November 24, 2021

    2.9K
    Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
    06:45

    Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

    Published on: October 28, 2022

    2.0K
    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

    5.3K

    Area of Science:

    • Control Systems Engineering
    • Fuzzy Logic Systems
    • Nonlinear Control Theory

    Background:

    • Interval type-2 Takagi-Sugeno (IT-2 T-S) fuzzy systems are widely used for modeling complex nonlinear systems.
    • Reliable sampled-data control is crucial for systems where control signals are updated at discrete time intervals.
    • Existing methods often do not fully utilize information within the sampling interval for robust control design.

    Purpose of the Study:

    • To investigate the stabilization problem of IT-2 T-S fuzzy-based reliable sampled-data control systems.
    • To develop a control design that considers information from the entire sampling interval.
    • To ensure global asymptotic stability for these complex systems.

    Main Methods:

    • Designing a reliable sampled-data controller for IT-2 T-S fuzzy systems.
    • Utilizing augmented state vectors and information across the entire sampling interval.
    • Constructing a looped Lyapunov-Krasovskii functional (LKF) incorporating fuzzy membership function derivatives.
    • Deriving stability conditions in the form of linear matrix inequalities (LMIs).

    Main Results:

    • Sufficient conditions for global asymptotic stability were derived using LMIs.
    • The proposed control technique ensures stability for IT-2 T-S fuzzy systems.
    • The effectiveness of the developed control method was demonstrated through simulations on three practical systems.

    Conclusions:

    • The developed reliable sampled-data control technique effectively stabilizes IT-2 T-S fuzzy systems.
    • The approach offers superior performance compared to existing methods.
    • The LMI-based conditions provide a systematic way to design robust controllers for such systems.