DocumentCode
1599663
Title
System identification through neuro-fuzzy methodologies
Author
Cucè, A. ; D´Angelo, G. ; Di Guardo, M. ; Giacalone, B. ; Mazzaglia, S. ; Vinci, C.
Author_Institution
SGS-Thomson Microelectron., Catania, Italy
fYear
1996
Firstpage
129
Lastpage
138
Abstract
The aim of the present work is to propose a way to identify the behaviour of an induction motor supplied by using a DC/AC converter controlled through a pulse width modulation (PWM) technique. Although a mathematical description of the motor is well-known in literature, the model is sensitive to parameters variations. Moreover it is impossible to modelize in a mathematical way the system composed by the motor and the inverter together. A neuro fuzzy network, trained with a set of I/O measures, it is able to identify the whole system. The results proposed show how the behaviour of the identified system matches the real one
Keywords
DC-AC power convertors; PWM invertors; PWM power convertors; fuzzy neural nets; identification; induction motors; DC/AC converter; I/O measures; PWM control; induction motor; inverter; neuro-fuzzy methodologies; pulse width modulation; system identification; Differential equations; Fuzzy neural networks; Fuzzy sets; Fuzzy systems; Induction motors; Mathematical model; Neural networks; Pulse width modulation; Pulse width modulation converters; System identification;
fLanguage
English
Publisher
ieee
Conference_Titel
Neuro-Fuzzy Systems, 1996. AT'96., International Symposium on
Conference_Location
Lausanne
Print_ISBN
0-7803-3367-5
Type
conf
DOI
10.1109/ISNFS.1996.603830
Filename
603830
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