Neural network based control of AC-AC converter for voltage sags, harmonics and EMI reduction

Abstract

A Neural Network based AC-AC voltage restorer is proposed for voltage sags and PWM type active power filter is used for voltage harmonics compensation and EMI reduction. The objective is to apply the neural network switching control technique to the AC-AC voltage restorer to reduce time delays during the switching conditions and switching losses. The aim of the IGBTs used in the AC-AC voltage restorer is to test and to find the best switching frequency-power combination in the steps of the simulation. Thus, the proposed AC-AC voltage restorer has some advantages such as fast switching response, simplicity and more intelligent structure, better output waveform. Neural Network techniques have proven that they were suitable for parameter identification and control of nonlinear systems. The transient condition of the AC-AC voltage restorer is improved via the Neural Network based control technique. On the other side, the proposed strategy for elimination of voltage harmonics using PWM type DC-AC inverter part of the system as an active filter. The last objective of the system is ElectroMagnetic Interference (EMI) reduction with using this filter and voltage restorer.