A new switching table based neural network for direct power control of three-phase PWM-rectifier Online publication date: Fri, 29-May-2020
by Arezki Fekik; Hakim Denoun; Mustapha Zaouia; Mohamed Lamine Hamida; Sundarapandian Vaidyanathan
International Journal of Modelling, Identification and Control (IJMIC), Vol. 33, No. 4, 2019
Abstract: Direct power control (DPC) is one of the newest techniques to control the PWM converter without network voltage sensors. This control technique is built on the idea of direct torque control (DTC) for an induction motor, which is applied to eliminate the harmonic of the line current and to compensate the reactive power. The principle of this control is based on instant active and reactive power loops. This article proposes an intelligent control approach to improve this control technique, such as artificial neural network (ANN), applied to the switching table. The comparison with conventional DPC shows that the use of 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 results proved the excellent performance of the proposed DPC scheme in comparison with the conventional DPC.
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