Name
Abstract | ||
|---|---|---|
A new algorithm for state observation based on a Neo-Fuzzy-Neuron (NFN) with real time training is presented. Some useful theorems are promptly demonstrated and used to aid the design of the observer. Two applications of this state observer are shown: an induction machine rotor flux observer and an induction machine speed observer. Digital simulation and experimental results show the good performance of the observer. |
Year | DOI | Venue |
|---|---|---|
2000 | 10.1109/SBRN.2000.889738 | Rio de Janeiro, RJ |
Keywords | DocType | ISSN |
digital simulation,electric current control,fuzzy neural nets,fuzzy systems,induction motors,learning (artificial intelligence),machine control,observers,velocity control,induction machine rotor flux observer,induction machine speed observer,online neo-fuzzy-neuron state observer,real time training,real time,torque,neural networks,state observer,learning artificial intelligence,computational intelligence | Conference | 1522-4899 |
ISBN | Citations | PageRank |
0-7695-0856-1 | 1 | 0.37 |
References | Authors | |
4 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Regis Pinheiro Landim | 1 | 18 | 5.18 |
| Benjamim R. de Menezes | 2 | 14 | 1.55 |
| Selênio R. Silva | 3 | 3 | 1.18 |
| Walmir M. Caminhas | 4 | 11 | 1.42 |