Induction motor drive with field-oriented control and speed estimation using feedforward neural network
| Autor: | Petr Palacky, Jan Strossa, Jakub Baca, Daniel Kouril |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Rotary encoder
Vector control Artificial neural network Computer science 020209 energy 020208 electrical & electronic engineering Feed forward 02 engineering and technology Control theory Control system 0202 electrical engineering electronic engineering information engineering Feedforward neural network Digital signal controller Induction motor |
| Zdroj: | 2020 21st International Scientific Conference on Electric Power Engineering (EPE). |
| DOI: | 10.1109/epe51172.2020.9269215 |
| Popis: | The paper presents the results of our research on the use of artificial neural networks for sensorless control of induction motor drives. A feedforward artificial neural network with one hidden layer was designed and trained offline to act as a model of induction motor, which directly provides the actual speed of a drive. The model was subsequently incorporated in the field-oriented control scheme, where it fully replaces an incremental encoder. The presented solution was tested out using an experimental drive equipped with a 2.2 kW induction machine and controlled by a control system which is based on the TMS320F28335 digital signal controller. The obtained experimental results show a high level of accuracy in the low speed range. |
| Databáze: | OpenAIRE |
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