Model Free Predictive Current Control Based on a Grey Wolf Optimizer for Synchronous Reluctance Motors

A Model-based predictive current control (MBPCC) has recently become a powerful advanced technology in industrial drives. However, MBPCC relies on the knowledge of system model and parameters, being, therefore, very sensitive to parameters errors. In case synchronous reluctance motor (SynRM), where vary due its ferromagnetic structure nonlinear magnetic properties, performance would suffer significantly. Accordingly, this paper, Grey Wolf Optimizer based model-free (GW-MFPCC) SynRM is proposed, skip all effects dependency uncertainty. The proposed method predicts stator through tracking minimum cost function using grey wolf optimizer. GW-MFPCC scheme compared MBPCC, effectiveness evaluated confirmed by experimental results.