You are in:Home/Publications/Fekik A, Denoun H, Azar AT, Zaouia M, Benyahia N, Hamida ML, Benamrouche N, Vaidyanathan S (2018) Artificial Neural Network for PWM Rectifier Direct Power Control and DC Voltage Control. Advances in System Dynamics and Control, pp. 286-314, IGI-Global, USA. DOI: 10.4018/978-1-5225-4077-9.ch010

Dr. Assoc. Prof. Ahmad Taher Azar :: Publications:

Title:
Fekik A, Denoun H, Azar AT, Zaouia M, Benyahia N, Hamida ML, Benamrouche N, Vaidyanathan S (2018) Artificial Neural Network for PWM Rectifier Direct Power Control and DC Voltage Control. Advances in System Dynamics and Control, pp. 286-314, IGI-Global, USA. DOI: 10.4018/978-1-5225-4077-9.ch010
Authors: Not Available
Year: 2018
Keywords: Not Available
Journal: Advances in System Dynamics and Control
Volume: Not Available
Issue: Not Available
Pages: 286-314
Publisher: IGI-Global, USA
Local/International: International
Paper Link:
Full paper Not Available
Supplementary materials Not Available
Abstract:

In this chapter, a new technique has been proposed for reducing the harmonic content of a three-phase PWM rectifier connected to the networks with a unit power factor and also providing decoupled control of the active and reactive instantaneous power. This technique called direct power control (DPC) is based on artificial neural network (ANN) controller, without line voltage sensors. The control technique is based on well-known direct torque control (DTC) ideas for the induction motor, which is applied to eliminate the harmonic of the line current and compensate for the reactive power. The main idea of this control is based on active and reactive power control loops. The DC voltage capacitor is regulated by the ANN controller to keep it constant and also provides a stable active power exchange. The simulation results are very satisfactory in the terms of stability and total harmonic distortion (THD) of the line current and the unit power factor.

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