Particle Swarm Based Approach of a Real-Time Discrete Neural Identifier for Linear Induction Motors
Joint Authors
López-Franco, Carlos
Rivera, Jorge
Rangel, E.
Arana-Daniel, Nancy
Alanis, Alma Y.
Source
Mathematical Problems in Engineering
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-12-29
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Alanis, Alma Y.& Rangel, E.& Rivera, Jorge& Arana-Daniel, Nancy& López-Franco, Carlos. 2013. Particle Swarm Based Approach of a Real-Time Discrete Neural Identifier for Linear Induction Motors. Mathematical Problems in Engineering،Vol. 2013, no. 2013, pp.1-9.
https://search.emarefa.net/detail/BIM-1032109
Modern Language Association (MLA)
Alanis, Alma Y.…[et al.]. Particle Swarm Based Approach of a Real-Time Discrete Neural Identifier for Linear Induction Motors. Mathematical Problems in Engineering No. 2013 (2013), pp.1-9.
https://search.emarefa.net/detail/BIM-1032109
American Medical Association (AMA)
Alanis, Alma Y.& Rangel, E.& Rivera, Jorge& Arana-Daniel, Nancy& López-Franco, Carlos. Particle Swarm Based Approach of a Real-Time Discrete Neural Identifier for Linear Induction Motors. Mathematical Problems in Engineering. 2013. Vol. 2013, no. 2013, pp.1-9.
https://search.emarefa.net/detail/BIM-1032109
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1032109