José Raimundo Dantas Neto

Mr. José Raimundo Dantas Neto

orcid

Research Focus & Metrics

Academic Career Length

3Years (2024-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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22 February 2024 in Energies
Verified
Journal Article
Open access
PDF file
José Raimundo Dantas NetoJosé Raimundo Dantas Neto
José Raimundo Dantas Neto
JLJosé Soares Batista Soares Batista Lopes
José Soares Batista Soares Batista Lopes
DMDiego Moura
Diego Moura
AGAntonio Ronaldo Gomes Garcia
Antonio Ronaldo Gomes Garcia
JFJossana Maria de Souza Ferreira
Jossana Maria de Souza Ferreira
Andres Ortiz SalazarAndres Ortiz Salazar
Andres Ortiz Salazar
This article describes the study and digital implementation of a system onboard a TMS 3208F28335 ® DSP for vector control of the bearing motor speed with four poles split winding with 250 W of power. Smart techniques: ANFIS and Neural Networks were investigated and computationally implemented to evaluate the bearing motor performance under the following conditions: operating as an estimator of uncertain parameters and as a speed controller. Therefore, the MATLAB program and its toolbox were used for the simulations and the parameter adjustments involving the structure ANFIS (Adaptive-Network-Based Fuzzy Inference System) and simulations with the Neural Network. The simulated results showed a good performance for the two techniques applied differently: the estimator and a speed controller using both a model of the induction motor operating as a bearing motor. The experimental part for velocity vector control uses three control loops: current, radial position, and speed, where the configurations of the peripherals, that is, the interfaces or drivers for driving the bearing motor.

4 January 2024 in Preprints.org
Verified
Preprint
Open access
PDF file
José Raimundo Dantas NetoJosé Raimundo Dantas Neto
José Raimundo Dantas Neto
JLJosé Soares Batista Soares Batista Lopes
José Soares Batista Soares Batista Lopes
DMDiego Moura
Diego Moura
AGAntonio Ronaldo Gomes Garcia
Antonio Ronaldo Gomes Garcia
JFJossana Maria de Souza Ferreira
Jossana Maria de Souza Ferreira
Andres Ortiz SalazarAndres Ortiz Salazar
Andres Ortiz Salazar
This article describes the study and digital implementation of a system onboard a TMS 3208F28335 ® DSP for vector control of the bearing motor speed with 4 poles split winding with 250W of power. Smart techniques: ANFIS and Neural Networks were investigated and computationally implemented to evaluate the bearing motor performance under the following conditions: operating as an estimator of uncertain parameters and as a speed controller. Therefore, the MATLAB program and its toolbox were used for the simulations and the parameter adjustments involving the structure ANFIS (Adaptive-Network-Based Fuzzy Inference System) and simulations with the Neural Network. The simulated results showed a good performance for the two techniques applied differently: the estimator and a speed controller using both a model of the induction motor operating as a bearing motor. The experimental part for velocity vector control uses three control loops: current, radial position, and speed, where the configurations of the peripherals, that is, the interfaces or drivers for driving the bearing motor.