Información del artículo
Resumen
Los modelos orientados a bloques han mostrado ser útiles y eficaces como representaciones no lineales en muchas aplicaciones. Son modelos simples y a la vez válidos en una región más amplia que un modelo lineal invariante en el tiempo. En cuanto a su estructura, consisten en una cascada integrada por una dinámica lineal y un bloque estático no lineal.
Si bien existen en la literatura numerosos trabajos que abordan la identificación nominal de estos modelos, el problema de identificación robusta en presencia de incertidumbre no ha sido cabalmente tratado.
En este trabajo, se consideran dos clases de modelos orientados a bloques: modelos Wiener y Hammerstein. Empleando una representación paramétrica, se propone describir la incertidumbre como un conjunto de parámetros, cuyos valores se obtienen resolviendo un problema de optimización. El algoritmo de identificación desarrollado se ilustra mediante ejemplos de simulación.
Palabras clave:
Wiener
Hammerstein
Identificación
Incertidumbre
Optimización
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