Direct Torque and Flux Control of Dual Stator Winding Induction Motor Drives based on Emotional Controller

Abstract

Recently, Dual Stator Winding Induction Machines (DSWIMs) has attracted the attention of many researchers. These induction machines which have two sets of three phase windings with unequal pole pairs and standard squirrel cage rotors, can overcome the associated complications of conventional three phase induction machines in zero speed operation regions. Generally, having unequal pole pairs brings the ability of independent operation of winding sets and accurately flux estimation in various rotor speed ranges. This paper proposes a direct torque and flux control system for DSWIMs based on Brain Emotional Learning Based Intelligent Controllers (BELBICs). These controllers which are model and parameter independent, are auto learning and adaptive. Indeed, in the proposed DSWIM-drive system the reference values for d and q axis voltages of stator winding sets are determined through BELBICs to directly control flux and torque of each winding sets. The reference value of winding fluxes is determined to minimize the stator currents and the torque commands are assigned by a torque sharing algorithm which enables the DSWIM to operate in a wide speed region, ranging from nominal positive to nominal negative. The proposed control system simulation in MATLAB/SIMULINK verifies its excellent performance in various speed ranges including zero speed.