Resumen

QUIROGA, JABID; CARTES, DAVID  y  EDRINGTON, CHRIS. NEURAL NETWORK BASED SYSTEM IDENTIFICATION OF A PMSM UNDER LOAD FLUCTUATION. Dyna rev.fac.nac.minas [online]. 2009, vol.76, n.160, pp.273-282. ISSN 0012-7353.

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.

Palabras clave : System; Identification; PMSM; Neural Network; Recurrent Networks.

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