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Related Experiment Video

Updated: Sep 26, 2025

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
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Fuzzy-Affine-Model-Based Filtering Design for Continuous-Time Roesser-Type 2-D Nonlinear Systems.

Meng Wang, Hak-Keung Lam, Jianbin Qiu

    IEEE Transactions on Cybernetics
    |April 20, 2022
    PubMed
    Summary

    This study introduces a new filter design for 2-D nonlinear systems using Takagi-Sugeno (T-S) fuzzy models. The method ensures system stability and disturbance attenuation for improved performance.

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    Area of Science:

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

    Background:

    • Continuous-time Roesser-type 2-D nonlinear systems present significant control challenges.
    • Existing filtering designs often struggle with stability and disturbance attenuation in complex systems.
    • Takagi-Sugeno (T-S) fuzzy affine models offer a promising approach for approximating nonlinear dynamics.

    Purpose of the Study:

    • To design a piecewise affine (PWA) filter for 2-D Roesser-type nonlinear systems.
    • To guarantee asymptotic stability of the filtering error system.
    • To achieve a prescribed level of disturbance attenuation (H∞ performance).

    Main Methods:

    • Approximating 2-D Roesser nonlinear systems using T-S fuzzy affine models with norm-bounded uncertainties.
    • Partitioning the premise variable space into crisp and fuzzy regions.
    • Constructing piecewise Lyapunov functions and utilizing the S-procedure for stability analysis.
    • Employing the projection lemma and convexification techniques for filter design.

    Main Results:

    • Development of novel PWA H∞ filter design conditions.
    • Demonstration of asymptotic stability and guaranteed H∞ performance for the filtering error system.
    • Validation of the approach's effectiveness and reduced conservativeness compared to common Lyapunov function methods.

    Conclusions:

    • The proposed PWA H∞ filtering approach effectively addresses the challenges in 2-D nonlinear systems.
    • The method provides a less conservative and more effective solution than existing techniques.
    • Simulation studies confirm the practical applicability and performance of the developed filtering strategy.