Neural network based estimation of torque in induction motors for real-time applications
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Data
2005-04-01
Autores
Goedtel, A.
Da Silva, I. N.
Serni, PJA
Título da Revista
ISSN da Revista
Título de Volume
Editor
Taylor & Francis Inc
Resumo
Induction motors are largely used in several industry sectors. The selection of an induction motor has still been inaccurate because in most of the cases the load behavior in its shaft is completely unknown. The proposal of this article is to use artificial neural networks for torque estimation with the purpose of best selecting the induction motors rather than conventional methods, which use classical identification techniques and mechanical load modeling. Since proposed approach estimates the torque behavior from the transient to the steady state, one of its main contributions is the potential to also be implemented in control schemes for real-time applications. Simulation results are also presented to validate the proposed approach.
Descrição
Palavras-chave
induction motors, load modeling, neural networks, parameter estimation, system identification
Como citar
Electric Power Components and Systems. Philadelphia: Taylor & Francis Inc., v. 33, n. 4, p. 363-387, 2005.