ANFIS controller and DQ frame-based power optimization for grid-tied three phases converter

Abstract

The study proposes an effective optimization technique aimed at reducing power loss and improving energy conversion efficiency in a three-phase electrically linked converter by employing an adaptive neuro-fuzzy inference system (ANFIS) controller. The control strategy integrates ANFIS with Fourier direct-quadrature (DQ) cycle translation based on the synchronous reference frame theory (SRFT). This combination significantly enhances converter performance by ensuring precise line synchronization, efficient voltage regulation, and effective harmonic suppression, all while delivering faster dynamic responses. The approach also simplifies the control framework and enables independent regulation of reactive and active power, offering greater operational flexibility. Such converters play a critical role in transforming DC or AC power from the grid or renewable sources into compatible electrical energy suitable for distribution. The proposed ANFIS-based DQ frame control method provides an advanced solution for optimizing the operation of electrically interconnected three-phase power converters. The research demonstrates the method’s effectiveness through detailed MATLAB simulations, confirming improved stability, reduced losses, and superior overall system performance.