Intelligent Maximum Power Factor Searching Control Using Recurrent Chebyshev Fuzzy Neural Network Current Angle Controller for SynRM Drive System

In this project, to develop a high-performance Synchronous Reluctance Motor (SynRM) drive system, a novel Maximum Power Factor Control (MPFC) using a current angle controller with stator resistance and stator flux estimators is proposed. Firstly, a Traditional Maximum Power Factor Control (TMPFC) system using a saliency ratio of the SynRM to generate a fixed current angle command is described. Since the saliency ratio requires offline pre-preparation and can’t be adjusted automatically, it is difficult to improve the performance of the MPFC in different operating regions because of the increasing of manufacturing cost and time-consuming. 

Therefore, an intelligent-Maximum Power Factor Searching Control (MPFSC) using a Recurrent Chebyshev fuzzy neural network (RCFNN) current angle controller is developed for the speed control of a SynRM. In order to search the online optimal Power Factor (PF) points of the SynRM under different operating conditions, the RCFNN current angle controller is designed to produce the compensated current angle command. Moreover, a proportional-integral speed controller is adopted to generate the stator current magnitude command, and the proposed intelligent-MPFSC is employed to generate the current angle command. The proposed system is simulated in MATLAB/SIMULINK.

Keywords: Maximum Power Factor Control (MPFC), Traditional Maximum Power Factor Control (TMPFC), Recurrent Chebyshev fuzzy neural network (RCFNN) current angle controller, SynRM Drive.