Neural Network Based Switching State Selection for Direct Power Control of Three Phase PWM-Rectifier

Fekik A.

Denoun H.

Hamida M.L.

Azar A.T.

Atig M.

Zhu Q.M.

Artificial Intelligence

Software and Communications

Innovation, Entrepreneurship and Competitiveness

This article proposes an intelligent approach to the Direct Power Control technique of the PWM rectifier, this control technique improves the performance of PWM converter, called Direct Power Control Based on Artificial Neural Network (ANN), applied for the selection of the optimal control vector. DPC-ANN ensures smooth control of active and reactive power in all Sectors and reduces current ripple. Finally, the developed DPC was tested by simulation, the simulation results proved the excellent performance of the proposed DPC scheme. © 2018 IEEE.

Neural Network Based Switching State Selection for Direct Power Contro

Neural Network Based Switching State Selection for Direct Power Control of Three Phase PWM-Rectifier

Graph transformer for communities detection in social networks

S-shaped and V-shaped gaining-sharing knowledge-based algorithm for feature selection

Enhancing Parkinson's disease diagnosis accuracy through speech signal algorithm modeling

Deep stacked ensemble learning model for COVID-19 classification

Neural Network Based Switching State Selection for Direct Power Contro

Neural Network Based Switching State Selection for Direct Power Control of Three Phase PWM-Rectifier

Related Publications

Graph transformer for communities detection in social networks

S-shaped and V-shaped gaining-sharing knowledge-based algorithm for feature selection

Enhancing Parkinson's disease diagnosis accuracy through speech signal algorithm modeling

Deep stacked ensemble learning model for COVID-19 classification