Particle Swarm Based Approach of a Real-Time Discrete Neural Identifier for Linear Induction Motors

Alma Y. Alanis, E. Rangel, J. Rivera, N. Arana-Daniel and C. Lopez-Franco

Mathematical Problems in Engineering, 2013, vol. 2013, 1-9

Abstract:

This paper focusses on a discrete-time neural identifier applied to a linear induction motor (LIM) model, whose model is assumed to be unknown. This neural identifier is robust in presence of external and internal uncertainties. The proposed scheme is based on a discrete-time recurrent high-order neural network (RHONN) trained with a novel algorithm based on extended Kalman filter (EKF) and particle swarm optimization (PSO), using an online series-parallel con figuration. Real-time results are included in order to illustrate the applicability of the proposed scheme.

Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:715094

DOI: 10.1155/2013/715094

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