Por favor utiliza este link para citar o compartir este documento: http://repositoriodigital.academica.mx/jspui/handle/987654321/183758
Título: A Direct Adaptive Vector Neural Control of a Three-Phase Induction Motor
Palabras clave: Ingeniería
Modelling and Simulation
Induction Motor
Field Oriented Control
Direct Vector Control
Neural Networks
Levenberg - Marquardt Learning
Backpropagation
Editorial: Instituto Politécnico Nacional
Descripción: The paper proposes a complete neural solution to the direct vector control of three phase induction motor including realtime trained neural controllers for velocity, flux and torque, which permitted the speed up reaction to the variable load. The basic equations and elements of the direct field oriented control scheme are given. The control scheme is realized by nine feedforward neural networks learned by real-time Backpropagation or off-line Levenberg-Marquardt algorithms with data taken by PI-control simulations. The graphical results of modelling show a better performance of the neural control system with respect to the PI controlled system realizing the same general control scheme.
Other Identifiers: http://www.redalyc.org/articulo.oa?id=61412466005
Aparece en las Colecciones:Científica

Archivos de este documento:
No hay archivos asociados a este documento.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.