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

Control Systems01:10

Control Systems

1.9K
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...
1.9K
Control Systems: Applications01:25

Control Systems: Applications

1.2K
Electrical engineering plays a pivotal role in our daily lives, with control systems at the heart of many applications, from home appliances to sophisticated space shuttles. Control systems manage and regulate the behavior of devices and processes, ensuring they function safely, correctly, and efficiently.
In modern vehicles, control systems manage various functions to enhance performance and safety. The steering wheel and accelerator are primary inputs in a car's control system. The...
1.2K
Feedback control systems01:26

Feedback control systems

725
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...
725
Classification of Titrimetric Analysis Based on Reaction Types01:01

Classification of Titrimetric Analysis Based on Reaction Types

1.8K
Titrimetric analysis in solution chemistry involves measuring the volume of solutions and is often called volumetric analysis. The standard solution of known concentration in the burette is called the titrant, whereas the solution of unknown concentration in the flask is called the analyte, or titrand. Titrimetric analyses can be classified into four types based on the reactions between the titrant and analyte.
Titrations between an acid and a base lead to neutralization reactions that form...
1.8K
Open and closed-loop control systems01:17

Open and closed-loop control systems

1.7K
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...
1.7K
Transfer Function in Control Systems01:21

Transfer Function in Control Systems

1.6K
The transfer function is a fundamental concept in the analysis and design of linear time-invariant (LTI) systems. It offers a concise way to understand how a system responds to different inputs in the frequency domain. It serves as a bridge between the time-domain differential equations that describe system dynamics and the frequency-domain representation that facilitates easier manipulation and analysis.
To derive the transfer function, consider a general nth-order linear time-invariant...
1.6K

You might also read

Related Articles

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

Sort by
Same author

A land-sea coupled framework for revealing hierarchical drivers of mangrove dynamics.

Journal of environmental management·2026
Same author

Diversity of stem endophytes communities from wild asparagus resources and the biocontrol potential on Phomopsis asparagi.

BMC microbiology·2026
Same author

Excitonic Shift Current in Monolayer MoS<sub>2</sub>.

ACS nano·2026
Same author

Knockdown of PTEN Inhibits Autophagy-Dependent Ferroptosis to Alleviate LPS-Induced Sepsis-Associated Acute Kidney Injury.

Inflammation·2026
Same author

FOXA1-mediated CEPT1 deficiency in airway epithelium drives asthma via an ER stress-mitochondrial dysfunction axis.

Cell reports·2026
Same author

Deep learning-based prediction of lymph node metastasis and occult tumor cells in gastric cancer using histopathological images: a retrospective study.

British journal of cancer·2026

Related Experiment Video

Updated: Feb 8, 2026

Microwave Photonics Systems Based on Whispering-gallery-mode Resonators
12:18

Microwave Photonics Systems Based on Whispering-gallery-mode Resonators

Published on: August 5, 2013

17.5K

Admissibility Analysis for Interval Type-2 Fuzzy Descriptor Systems Based on Sliding Mode Control.

Xingjian Sun, Qingling Zhang

    IEEE Transactions on Cybernetics
    |July 12, 2018
    PubMed
    Summary

    This study introduces a novel sliding mode control for nonlinear singular systems using interval type-2 fuzzy models. The method minimizes system chattering while ensuring guaranteed H∞ performance.

    More Related Videos

    Behavioral Assessment of Hearing in 2 to 4 Year-old Children: A Two-interval, Observer-based Procedure Using Conditioned Play-based Responses
    14:05

    Behavioral Assessment of Hearing in 2 to 4 Year-old Children: A Two-interval, Observer-based Procedure Using Conditioned Play-based Responses

    Published on: January 23, 2017

    29.7K
    Isolation and Transcriptome Analysis of Plant Cell Types
    08:53

    Isolation and Transcriptome Analysis of Plant Cell Types

    Published on: April 7, 2023

    2.2K

    Related Experiment Videos

    Last Updated: Feb 8, 2026

    Microwave Photonics Systems Based on Whispering-gallery-mode Resonators
    12:18

    Microwave Photonics Systems Based on Whispering-gallery-mode Resonators

    Published on: August 5, 2013

    17.5K
    Behavioral Assessment of Hearing in 2 to 4 Year-old Children: A Two-interval, Observer-based Procedure Using Conditioned Play-based Responses
    14:05

    Behavioral Assessment of Hearing in 2 to 4 Year-old Children: A Two-interval, Observer-based Procedure Using Conditioned Play-based Responses

    Published on: January 23, 2017

    29.7K
    Isolation and Transcriptome Analysis of Plant Cell Types
    08:53

    Isolation and Transcriptome Analysis of Plant Cell Types

    Published on: April 7, 2023

    2.2K

    Area of Science:

    • Control Systems Engineering
    • Fuzzy Logic Systems
    • Nonlinear System Analysis

    Background:

    • Nonlinear singular systems present significant control challenges.
    • Interval Type-2 (IT2) fuzzy models offer enhanced approximation capabilities for nonlinear systems.
    • Modeling errors and uncertainties in membership functions require careful consideration.

    Purpose of the Study:

    • To develop a robust sliding mode control strategy for nonlinear singular systems.
    • To incorporate interval type-2 fuzzy models to accurately represent system nonlinearities and uncertainties.
    • To minimize system chattering and guarantee H∞ performance.

    Main Methods:

    • Utilizing an interval type-2 (IT2) fuzzy model to approximate nonlinear systems, including modeling errors.
    • Expressing uncertainties in membership functions based on their boundedness.
    • Deriving admissibility conditions using a linear matrix inequalities (LMI) approach.
    • Designing a novel reaching law-based sliding mode controller with distinct input gains.

    Main Results:

    • Admissibility conditions for the IT2 fuzzy singular system were successfully obtained.
    • A new sliding mode controller was designed to minimize chattering.
    • Guaranteed H∞ performance was achieved for the closed-loop system.
    • Simulation results verified the effectiveness and feasibility of the proposed control method.

    Conclusions:

    • The proposed interval type-2 fuzzy sliding mode control is effective for nonlinear singular systems.
    • The controller successfully addresses modeling errors and uncertainties.
    • The method provides robust performance with minimized chattering and guaranteed H∞ stability.