Comparation of PI and Neural Fuzzy Based Closed Loop Control Methods for Permanent Magnet Synchronous Motor Fed by Matrix Converter

Abstract

Permanent magnet synchronous machines are used in many industrial applications today. In particular, depending on the developments in magnetic materials, permanent magnet synchronous motors rapidly developing in recent years have found themselves a widespread coverage in applications because of their outstanding features. When the research in the literature is surveyed, it is observed that the vector control of electrical machines is done by means of various methods. One of the most common applications of artificial intelligence used in the analysis of electrical machines is Neuro-Fuzzy, a combination of Fuzzy Logic and Neural Network. In this paper, the vector control of PMSM fed by a matrix converter is modeled and simulated by using PI controllers and Neuro-Fuzzy, one of the intelligent methods. Waveforms derived from the simulation of the vector control of PMSM fed by a matrix converter were examined comparatively for PI and Neuro-fuzzy controllers.