dc.contributor | Universidade de São Paulo (USP) | |
dc.contributor | Universidade Estadual Paulista (Unesp) | |
dc.date.accessioned | 2020-12-10T18:06:05Z | |
dc.date.accessioned | 2022-12-19T20:09:49Z | |
dc.date.available | 2020-12-10T18:06:05Z | |
dc.date.available | 2022-12-19T20:09:49Z | |
dc.date.created | 2020-12-10T18:06:05Z | |
dc.date.issued | 2006-01-01 | |
dc.identifier | 2006 Ieee International Conference On Power Electronic, Drives And Energy Systems, Vols 1 And 2. New York: Ieee, p. 926-+, 2006. | |
dc.identifier | http://hdl.handle.net/11449/195870 | |
dc.identifier | WOS:000245596300170 | |
dc.identifier.uri | https://repositorioslatinoamericanos.uchile.cl/handle/2250/5376507 | |
dc.description.abstract | The use of sensorless technologies is an increasing tendency on industrial drivers for electrical machines. The estimation of electrical and mechanical parameters involved with the electrical machine control. is used very frequently in order to avoid measurement of all variables involved in this process. The cost reduction may also be considered in industrial drivers, besides the increasing robustness of the system, as an advantage of the use of sensorless technologies. This work proposes the use of artificial neural networks to estimate one of the most important variables in the induction motor control schemes: the speed. Simulation results are presented to validate the proposed approach. | |
dc.language | eng | |
dc.publisher | Ieee | |
dc.relation | 2006 Ieee International Conference On Power Electronic, Drives And Energy Systems, Vols 1 And 2 | |
dc.source | Web of Science | |
dc.title | Speed estimation for sensorless technology using recurrent neural networks and single current sensor | |
dc.type | Actas de congresos | |