Parametric and Non-parametric Mathematical Modelling Techniques: A Practical Approach of an Electrical Machine Identification

Oscar Gonzales

doi:10.46480/esj.5.1.86

Autores/as

Oscar Gonzales Instituto Superior Tecnológico Sucre

DOI:

https://doi.org/10.46480/esj.5.1.86

Palabras clave:

Modelo paramétrico, Modelo no paramétrico, Datos experimentales, Modelado, Identificación

Resumen

El modelado matemático es una característica muy importante en relación con el análisis y control de sistemas dinámicos. Además, la identificación del sistema es un enfoque para construir expresiones matemáticas a partir de datos experimentales tomados de procesos. En este contexto, este trabajo describe varias técnicas de modelado e identificación que son herramientas poderosas para determinar el comportamiento de los sistemas dinámicos en el tiempo. En Este trabajo se enfatiza las principales ventajas y/o desventajas que tienen las diferentes formulaciones matemáticas de modelación e identificación. También se presenta una revisión exhaustiva de las principales técnicas de modelado e identificación desde una perspectiva paramétrica y no paramétrica. Se formularon los modelos paramétricos y no paramétricos por medio de sus ecuaciones para aplicarlos en un caso de estudio. Los datos experimentales se toman de una máquina eléctrica, un motor de DC de una plataforma didáctica en la cual se aplican un conjunto de entradas conocidas para medir la velocidad del motor y utilizar estos datos como parte del proceso de modelación e identificación. El artículo concluye con las soluciones proporcionadas por la comparación de técnicas de modelación e identificación donde soluciones sencillas como los sistemas de primer orden son precisos para modelar un motor DC de dinámica lineal sobre otras formulaciones matemáticas más complejas

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