Design and implementation of Type-2 fuzzy neural system controller for PWM rectifiers

Abstract

It is necessary to convert AC to DC for the systems that do not work with AC sources. For this reason, diode and thyristor rectifiers were developed and designed. However, these rectifiers are not well suited for industrial applications requiring high performance. With the advances in power electronics and semiconductor technology, Pulse width modulation (PWM) rectifiers have been successfully employed in various industrial applications including variable-speed drives and uninterruptible power supplies. PWM rectifiers have the advantages of being low input current harmonic, adjustable input power factor, and controllable DC voltage and bidirectional energy flow. Because of all these features of the PWM rectifiers, the control and design of these rectifiers are very important topic. The aim of this paper is to control DC-link voltage of PWM rectifier with type-2 fuzzy neural system (T2FNS) instead of PI controller. For this aim, three-phase PWM rectifier with proposed controller is designed and simulated for four scenarios in this paper. A simulation model of the PWM rectifier is designed in MATLAB/Simulink and the performance of PWM rectifier with proposed controller is analyzed. (c) 2017 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.