Parameters Identification of the Fractional-Order Permanent Magnet Synchronous Motor Models Using Chaotic Ensemble Particle Swarm Optimizer

In this paper, novel variants for the Ensemble Particle Swarm Optimizer (EPSO) are proposed where ten chaos maps merged to enhance EPSO’s performance by adaptively tuning its main parameters. The Chaotic (C.EPSO) examined with complex nonlinear systems concerning equal order and variable-order fractional models of Permanent Magnet Synchronous Motor (PMSM). variants’ results compared that original version recommend most suitable variant non-linear optimization problem. A comparison between introduced previously published algorithms proves developed technique’s efficiency further validation. emerge Gauss/mouse map is proper estimating parameters PMSM models, as it achieves better accuracy, higher consistency, faster convergence speed, may lead controlling motor’s unwanted chaotic protect from ravage.