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    Este estudio introduce un nuevo método para la estimación del estado en sistemas de salto de Markov 2D que enfrentan ataques de inyección de datos falsos. El enfoque mejora la robustez y la adaptabilidad del sistema para un rendimiento confiable.

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    Área de la Ciencia:

    • Ingeniería de sistemas de control
    • Procesamiento de señales
    • Ciberseguridad en los sistemas

    Sus antecedentes:

    • La estimación del estado es crucial para los sistemas de salto de Markov en 2D.
    • Los ataques aleatorios de inyección de datos falsos (FDIA) representan amenazas significativas para la integridad y el rendimiento del sistema.
    • Los métodos existentes pueden carecer de robustez frente a condiciones dinámicas de red y ataques sofisticados.

    Objetivo del estudio:

    • Desarrollar un método de estimación de estado robusto para los sistemas de salto de Markov en 2D bajo FDIA.
    • Mejorar la adaptabilidad y el rendimiento del sistema en entornos de red inciertos.
    • Para garantizar la estabilidad y la atenuación del ruido a pesar de la inyección maliciosa de datos.

    Principales métodos:

    • Propuso un nuevo mecanismo probabilístico de desencadenamiento de eventos de múltiples intervalos (PMIETP) que combina umbrales de subintervalos y modelos de probabilidad.
    • Desarrolló un estimador basado en el mecanismo de saturación variable en el tiempo (TVSM) con un umbral adaptativo para manejar datos anormales.
    • Utilizó la optimización de enjambres de partículas (PSO) para optimizar los parámetros de diseño y reducir la conservaduridad en condiciones de desigualdad de matriz lineal (LMI).
    • Se derivaron criterios suficientes basados en la teoría de la estabilidad de Lyapunov para la estabilidad asintótica cuadrada media y la atenuación del ruido.

    Principales resultados:

    • El PMIETP propuesto integrado con TVSM mitiga efectivamente el impacto del FDIA.
    • El enfoque demuestra una mayor adaptabilidad a las diferentes condiciones de la red y una mayor robustez de las estimaciones.
    • Las simulaciones numéricas confirman la eficacia y la superioridad del método propuesto sobre las técnicas existentes.

    Conclusiones:

    • El nuevo enfoque de estimación de estado basado en PMIETP y TVSM proporciona una solución robusta para los sistemas de salto de Markov en 2D bajo FDIA.
    • El método garantiza la estabilidad del sistema y las garantías de rendimiento, ofreciendo ventajas significativas en aplicaciones prácticas.
    • El estudio pone de relieve el potencial de los mecanismos de adaptación y los algoritmos de optimización para mejorar la seguridad de los sistemas de control.