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http://acervodigital.unesp.br/handle/11449/70676
- Title:
- Estimation of electrical machine speed using sensorless technology and neural networks
- University of Technology - Paraná (UTFPR-CP)
- Universidade de São Paulo (USP)
- Universidade Estadual Paulista (UNESP)
- 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 related to 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 a recurrent artificial neural network to estimate the speed of induction motor for sensorless control schemes using one single current sensor. Simulation and experimental results are presented to validate the proposed approach. ©2008 IEEE.
- 1-Dec-2008
- 2008 IEEE/PES Transmission and Distribution Conference and Exposition: Latin America, T and D-LA.
- Induction motors
- Neural networks
- System identification
- Current sensors
- Electrical machine
- Mechanical parameters
- Recurrent artificial neural networks
- Sensorless
- Sensorless control scheme
- Identification (control systems)
- Motors
- Recurrent neural networks
- Sensor networks
- http://dx.doi.org/10.1109/TDC-LA.2008.4641832
- Acesso restrito
- outro
- http://repositorio.unesp.br/handle/11449/70676
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