<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Ghoulemallah Boukhalfa</style></author><author><style face="normal" font="default" size="100%">Sebti Belkacem</style></author><author><style face="normal" font="default" size="100%">Abdesselem Chikhi</style></author><author><style face="normal" font="default" size="100%">Said Benaggoune</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Direct torque control of dual star induction motor using a fuzzy-PSO hybrid approach</style></title><secondary-title><style face="normal" font="default" size="100%">Applied Computing and InformaticsApplied Computing and Informatics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2018</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2018</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">This paper presents the particle swarm optimization (PSO) algorithm in conjuction with the fuzzy logic method in order to achieve an optimized tuning of a proportional integral derivative controller (PID) in the DTC control loops of dual star induction motor (DSIM). The fuzzy controller is insensitive to parametric variations, however, with the PSO-based optimization approach we obtain a judicious choice of the gains to make the system more robust. According to Matlab simulation, the results demonstrate that the hybrid DTC of DSIM improves the speed loop response, ensures the system stability, reduces the steady state error and enhances the rising time. Moreover, with this controller, the disturbances do not affect the motor performances.</style></abstract></record></records></xml>