Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Linear Approximation in Time Domain

Linear Approximation in Time Domain

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, the...

Linear Approximation in Frequency Domain

Linear Approximation in Frequency Domain

Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear.

Feedback control systems

Feedback control systems

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...

SFG Algebra

SFG Algebra

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...

State Space Representation

State Space Representation

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...

Controller Configurations

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...

You might also read

Related Articles

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

Sort by

Same author

The neural correlates of value hierarchies: a prospective typology based on personal value profiles of emerging adults.

Frontiers in psychology·2024

Same author

Efficacy and Safety of PF-07038124 in Patients With Atopic Dermatitis and Plaque Psoriasis: A Randomized Clinical Trial.

JAMA dermatology·2023

Same author

Improving enteral nutrition tolerance and protein intake maybe beneficial to intensive care unit patients.

Scientific reports·2023

Same author

Efficacy and Safety of Dual Anti-HER2 Blockade and Docetaxel With or Without Carboplatin as Neoadjuvant Regimen for Treatment of HER2-Positive Breast Cancer.

Technology in cancer research & treatment·2023

Same author

Boosting Low-Temperature CO<sub>2</sub> Hydrogenation over Ni-based Catalysts by Tuning Strong Metal-Support Interactions.

Angewandte Chemie (International ed. in English)·2023

Same author

A new direction in Chinese herbal medicine ameliorates for type 2 diabetes mellitus: Focus on the potential of mitochondrial respiratory chain complexes.

Journal of ethnopharmacology·2023

Same journal

Strategic Ability Updating in Concurrent Games by Coalitional Commitment.

IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society·2015

Same journal

Meta-Analysis of the First Facial Expression Recognition Challenge.

IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society·2012

Same journal

Adjustable model-based fusion method for multispectral and panchromatic images.

IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society·2012

Same journal

Face Feature Weighted Fusion Based on Fuzzy Membership Degree for Video Face Recognition.

IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society·2012

Same journal

A New Adaptive Fast Cellular Automaton Neighborhood Detection and Rule Identification Algorithm.

IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society·2012

Same journal

Human-arm-and-hand-dynamic model with variability analyses for a stylus-based haptic interface.

IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society·2012

See all related articles

Search research articles

Related Experiment Video

Updated: May 23, 2026

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

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

T-S-Fuzzy-Model-Based Approximation and Controller Design for General Nonlinear Systems.

Qing Gao, Xiao-Jun Zeng, Gang Feng

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society

|March 22, 2012

Summary

This summary is machine-generated.

This study introduces a new method for controlling nonlinear systems using Takagi-Sugeno (T-S) fuzzy models. The approach converts nonlinear control problems into robust stabilization tasks solvable with linear matrix inequalities.

Related Experiment Videos

Last Updated: May 23, 2026

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

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

Area of Science:

Control Theory
Fuzzy Systems
Nonlinear Dynamics

Background:

General nonlinear systems pose significant control challenges.
Existing methods may lack accuracy or broad applicability.
Takagi-Sugeno (T-S) fuzzy models offer a framework for approximating nonlinear dynamics.

Purpose of the Study:

To develop a novel approach for controlling general nonlinear systems.
To demonstrate the approximation capability of generalized T-S fuzzy models.
To solve the stabilization and H∞ control problems for nonlinear systems.

Main Methods:

Approximation of general nonlinear systems using generalized T-S fuzzy models.
Formulation of the stabilization problem as a robust stabilization problem.
Utilizing piecewise quadratic Lyapunov functions and linear matrix inequalities (LMIs).

Main Results:

General nonlinear systems can be accurately approximated by generalized T-S fuzzy models.
Robust semiglobal stabilization and H∞ control are achieved.
The proposed method effectively handles approximation errors as uncertainties.

Conclusions:

The proposed T-S fuzzy model-based approach provides an effective framework for nonlinear system control.
LMIs offer a computationally tractable method for designing controllers.
Simulation results validate the practical applicability of the developed control strategies.