Neural network based system identification of a pmsm under load fluctuation

A neural network based approach is applied to model a PMSM. A multilayer recurrent network provides a near term fundamental current prediction using as an input the fundamental components of the voltage signals and the speed. The PMSM model proposed can be implemented in a condition based maintenanc...

Full description

Autores:
Quiroga Méndez, Jabid Eduardo
Cartes, David
Edrington, Chris
Tipo de recurso:
Article of journal
Fecha de publicación:
2009
Institución:
Universidad Nacional de Colombia
Repositorio:
Universidad Nacional de Colombia
Idioma:
spa
OAI Identifier:
oai:repositorio.unal.edu.co:unal/26910
Acceso en línea:
https://repositorio.unal.edu.co/handle/unal/26910
http://bdigital.unal.edu.co/17958/
Palabra clave:
System
Identification
PMSM
Neural Network
Recurrent Networks.
Rights
openAccess
License
Atribución-NoComercial 4.0 Internacional
Description
Summary:A neural network based approach is applied to model a PMSM. A multilayer recurrent network provides a near term fundamental current prediction using as an input the fundamental components of the voltage signals and the speed. The PMSM model proposed can be implemented in a condition based maintenance to perform fault detection, integrity assessment and aging process. The model is validated using a 15 hp PMSM experimental setup. The acquisition system is developed using Matlab®/Simulink® with dSpace® as an interface to the hardware, i.e. PMSM drive system. The model shows generalization capabilities and a satisfactory performance in the fundamental current determination on line under no load and load fluctuations.