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

作者：Alanis Alma Y^*; Rangel E; Rivera J; Arana Daniel N; Lopez Franco C

来源：Mathematical Problems in Engineering, 2013, 2013: 715094.

DOI：10.1155/2013/715094

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 configuration. Real-time results are included in order to illustrate the applicability of the proposed scheme.

• 出版日期2013