Robust control of current controlled pwm rectifiers using type-2 fuzzy neural networks for unity power factor operation

Abstract

AC-DC conversion is a necessary for the systems that require DC source. This conversion has been done via rectifiers based on controlled or uncontrolled semiconductor switches. Advances in the power electronics and microprocessor technologies allowed the use of Pulse Width Modulation (PWM) rectifiers. In this paper, dq-axis current and DC link voltage of three-phase PWM rectifier are controlled by using type-2 fuzzy neural network (T2FNN) controller. For this aim, a simulation model is built by MATLAB/Simulink software. The model is tested under three different operating conditions. The parameters of T2FNN is updated online by using back-propagation algorithm. The results obtained from both T2FNN and Proportional + Integral + Derivate (PID) controller are given for three operating conditions. The results show that three-phase PWM rectifier using T2FNN provides a superior performance under all operating conditions when compared with PID controller. © The Korean Institute of Electrical Engineers.