A Hybrid Gray Wolf Optimizer for Modeling and Control of Permanent Magnet Synchronous Motor Drives

Abstract

AbstractThe model order diminution and controller design of the permanent magnet synchronous motor drive, which is commonly called PMSM, are performed in the complex delta framework using a hybrid metaheuristic algorithm. Two fundamental algorithms, viz., the firefly technique and the gray wolf optimizer (GWO) are combined to develop a new topology termed as the hybrid gray wolf optimizer (HGWO). A PMSM drive made up of both the speed and current controllers was originally generated, by using an identification method used for signal processing, to yield a lower-order model. The second-order model in cascade with an appropriate controller is thus compared with a chosen reference to estimate approximately the control parameters which are not known beforehand. The continuous parameters almost imitated the parameters set with the delta operator. Thus, for the drive, thereby, a unified control system is built. Therefore, both for order reduction and for calculating the control parameters of PMSM drives, the proposed algorithm is successfully used. Besides, a case study for the control of such special motor drives can also be investigated in the future for many household as well as commercial purposes.KeywordsPermanent magnet motorModel matchingDelta domain methodFirefly algorithm (FA)Gray wolf optimizer (GWO)Hybrid gray wolf optimizer (HGWO)