Harmonic reduction in PWM AC voltage controller using genetic algorithms and neural network

In this paper, a novel harmonic reduction technique in PWM AC voltage controller is proposed to reduce the harmonic contents in current waveform. Our technique is used to evaluate the optimal turn on and turn off angles in PWM such that the total current harmonic distortion is minimized. To accomplish this optimization tasks, in this paper, Genetic Algorithm (GA) is adopted. However, the evolved angles are only optimized at a given desired output voltage. To apply our proposed technique for all of output voltages, artificial neural network (ANN) is investigated to approximate the switching angles from sets of optimal angles evolved by GA. Simulation results show that our proposed technique is suited for designing and gains a better performance and reduction of current harmonics compared to conventional fixed-pulse PWM.