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Masking and Demasking Agents01:19

Masking and Demasking Agents

EDTA titrations may necessitate masking and demasking agents to temporarily protect a particular metal ion in a mixture from the EDTA reaction. These agents facilitate the sequential analysis of the metal ions by forming stable complexes with some—but not all—metal ions during certain steps.
There are many masking agents, such as cyanide, fluoride, triethanolamine, thiourea, and 2,3-bis(sulfanyl)propan-1-ol (formerly 2,3-dimercapto-1-propanol), with the masking agent chosen based on the metal...

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Updated: Jun 19, 2026

Memorization-Based Training and Testing Paradigm for Robust Vocal Identity Recognition in Expressive Speech Using Event-Related Potentials Analysis
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Task-Preserving EEG Anonymization Using Latent Feature Masking.

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    Summary
    This summary is machine-generated.

    This study introduces novel fuzzy control strategies for permanent magnet synchronous generator wind turbines, enhancing system stability and performance under varying conditions. The new approach improves sampling periods and overall system reliability.

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    Published on: November 1, 2019

    Area of Science:

    • Control Systems Engineering
    • Renewable Energy Systems
    • Fuzzy Logic Applications

    Background:

    • Wind turbine systems, particularly those using permanent magnet synchronous generators (PMSG), face challenges with state and output reachability due to nonlinear dynamics, disturbances, and parametric uncertainty.
    • Existing sampled-data control schemes often lack adaptability to time-varying sampling periods and network-induced uncertainties like packet dropouts.

    Purpose of the Study:

    • To develop novel time-dependent output-feedback and state-feedback sampled-data control strategies for PMSG-based wind turbines.
    • To achieve robust state and output reachability despite bounded disturbances, parametric uncertainty, and Bernoulli random packet dropouts.
    • To enhance the performance and stability of wind turbine systems through a unified fuzzy control framework.

    Main Methods:

    • A nonlinear wind turbine model is represented using fuzzy linear subsystems.
    • A unified, sampling time-dependent fuzzy control framework is designed for both state-feedback and output-feedback control.
    • A sampling variable-dependent discontinuous Lyapunov-Krasovskii functional is utilized.
    • A fuzzy membership function-dependent H-infinity technique is employed to derive reachability conditions.

    Main Results:

    • The proposed control strategies demonstrate applicability and effectiveness in simulation studies.
    • Improvements were observed in the allowable maximum sampling period compared to existing methods.
    • Reduced H-infinity performance bounds and tighter reachable-set ellipsoids were achieved.
    • The number of decision variables required for control design was reduced.

    Conclusions:

    • The developed fuzzy sampled-data control strategies offer a robust and improved approach for PMSG wind turbine systems.
    • The framework effectively handles time-varying sampling and packet dropouts, ensuring state and output reachability.
    • The results confirm significant performance enhancements, making the strategies suitable for practical implementation.