Name
Title | ||
|---|---|---|
Stator resistance identification based on neural and fuzzy logic principles in an induction motor drive |
Abstract | ||
|---|---|---|
This paper presents a method for stator resistance identification of an induction motor in an indirect rotor field-oriented control system. This method is based on a simple artificial neural network, in which the rotor time constant is no longer considered to be a constant parameter, but is instead identified using an adaptive model reference system-based procedure. The neural network outputs the estimated rotor speed. The difference between the actual and the estimated rotor speed is used as a signal for either manual or automated fuzzy logic stator resistance identification. Simulations and experiments show the effectiveness of the described approach. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1016/j.neucom.2009.06.017 | Neurocomputing |
Keywords | Field | DocType |
stator resistance identification,estimated rotor speed,fuzzy logic principle,neural network,simple artificial neural network,rotor time,resistance identification,indirect rotor field-oriented control,constant parameter,automated fuzzy logic stator,induction motor drive,adaptive model reference,time constant,induction motor,artificial neural network,field oriented control,fuzzy logic,adaptive control | Vector control,Induction motor,Control theory,Fuzzy logic,Rotor (electric),Control system,Stator,Adaptive control,Artificial neural network,Mathematics | Journal |
Volume | Issue | ISSN |
73 | 4-6 | Neurocomputing |
Citations | PageRank | References |
3 | 0.68 | 1 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dinko Vukadinovic | 1 | 4 | 2.28 |
| Mateo Basic | 2 | 4 | 1.94 |
| Ljubomir Kulisic | 3 | 4 | 1.94 |