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

Controller Configurations01:22

Controller Configurations

319
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...
319
Feedback control systems01:26

Feedback control systems

648
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...
648
PD Controller: Design01:26

PD Controller: Design

565
In automotive engineering, car suspension systems often employ Proportional Derivative (PD) controllers to enhance performance. PD controllers are utilized to adjust the damping force in response to road conditions. A controller, acting as an amplifier with a constant gain, demonstrates proportional control, with output directly mirroring input.
Designing a continuous-data controller requires selecting and linking components like adders and integrators, which are fundamental in Proportional,...
565
State Space Representation01:27

State Space Representation

485
The frequency-domain technique, commonly used in analyzing and designing feedback control systems, is effective for linear, time-invariant systems. However, it falls short when dealing with nonlinear, time-varying, and multiple-input multiple-output systems. The time-domain or state-space approach addresses these limitations by utilizing state variables to construct simultaneous, first-order differential equations, known as state equations, for an nth-order system.
Consider an RLC circuit, a...
485
SFG Algebra01:16

SFG Algebra

286
In Signal Flow Graph (SFG) algebra, the value a node represents is determined by the sum of all signals entering that node. This summed value is then transmitted through every branch leaving the node, making the SFG a powerful tool for visualizing and analyzing control systems.
Each node in an SFG corresponds to a variable, and the interactions between nodes are represented by branches with associated gains. When multiple branches lead into a node, the value at that node is the sum of the...
286
Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

301
Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
301

You might also read

Related Articles

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

Sort by
Same author

High-performance collision avoidance parallel parking strategy of the autonomous vehicle.

Fundamental research·2026
Same author

Control strategy design for the anti-HBV mathematical model.

IET systems biology·2019
Same author

Switching control strategy for the HIV dynamic system with some unknown parameters.

IET systems biology·2019
Same author

Polynomial Controller Synthesis for Uncertain Large-Scale Polynomial T-S Fuzzy Systems.

IEEE transactions on cybernetics·2019
Same author

Implementation of a ball inverted pendulum with omnidirectional moving ability using a robust fuzzy control strategy.

ISA transactions·2018
Same author

A novel synchronization scheme with a simple linear control and guaranteed convergence time for generalized Lorenz chaotic systems.

Chaos (Woodbury, N.Y.)·2013
Same journal

An Evolutionary Algorithm Assisted by an Ensemble of Pareto-Optimal Surrogate Models.

IEEE transactions on cybernetics·2026
Same journal

A Quantum Self-Attention Neural Network Model on Quantum Circuits.

IEEE transactions on cybernetics·2026
Same journal

Semi-Explicit Solution of Some Discrete-Time Higher-Order-Cost Mean-Field-Type Control.

IEEE transactions on cybernetics·2026
Same journal

A Novel One-Step Small Object Detector for Autonomous Aerial Vehicles.

IEEE transactions on cybernetics·2026
Same journal

Online Data-Driven-Based Optimal Output Tracking Control Without Initial Stabilizing Policy.

IEEE transactions on cybernetics·2026
Same journal

Digital Redesign-Based Interval State Estimation for Continuous Systems With Aperiodic Discrete Measurements.

IEEE transactions on cybernetics·2026
See all related articles

Related Experiment Video

Updated: Jan 3, 2026

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

5.0K

Decentralized Observer-Based Controller Synthesis for a Large-Scale Polynomial T-S Fuzzy System With Nonlinear

Van-Phong Vu, Wen-June Wang

    IEEE Transactions on Cybernetics
    |November 15, 2019
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a new decentralized controller for large-scale nonlinear systems using polynomial T-S fuzzy models. The method relaxes constraints on nonlinear interconnections, improving practical applicability for complex systems.

    More Related Videos

    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
    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

    5.4K

    Related Experiment Videos

    Last Updated: Jan 3, 2026

    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

    5.0K
    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
    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

    5.4K

    Area of Science:

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

    Background:

    • Large-scale nonlinear systems present significant control challenges due to complex interconnections.
    • Existing observer-based controllers often require strict bound constraints on nonlinear interconnection terms, limiting their applicability.
    • Polynomial T-S fuzzy systems offer a framework to model nonlinear systems while potentially reducing modeling errors and fuzzy rule complexity.

    Purpose of the Study:

    • To propose a novel decentralized observer-based controller for large-scale nonlinear systems with arbitrary nonlinear interconnections.
    • To develop a controller that does not require prior bounding of nonlinear interconnection terms, offering greater flexibility.
    • To design an observer capable of simultaneously estimating unmeasurable states and unknown nonlinear interconnection terms.

    Main Methods:

    • Modeling the large-scale nonlinear system using polynomial Takagi-Sugeno (T-S) fuzzy systems.
    • Developing a new observer form utilizing an unknown input method to estimate unmeasurable states and interconnection terms.
    • Employing Lyapunov functions and the sum-of-squares (SOS) technique to derive observer and controller design conditions.

    Main Results:

    • A decentralized observer-based controller was successfully synthesized for large-scale nonlinear systems.
    • The proposed method accommodates arbitrary nonlinear interconnection functions without requiring bound constraints.
    • The observer effectively estimates unmeasurable states and unknown interconnection terms, which are then used for system stabilization.
    • Two numerical examples validated the effectiveness and advantages of the proposed approach.

    Conclusions:

    • The developed observer-based controller provides a more relaxed and practical approach for controlling large-scale nonlinear systems.
    • The novel observer design, capable of estimating unknown states and interconnections, represents a significant advancement.
    • The method demonstrates potential for broader application in complex nonlinear system control where interconnection terms are difficult to bound.